Category: Data, Integration & Governance

Intelligent Orchestration: How Integrated Systems Drive Success

Posted on February 18, 2025 by - AI Transformation, Data, Integration & Governance

Enterprise silos slow businesses down, which makes them less competitive. When teams, data, and systems operate in isolation, workflows break down, decisions take longer, and customers feel the disconnect. 

A Forrester report found that knowledge workers lose an average of 12 hours per week searching for data instead of acting on it. That’s nearly a third of their workweek wasted. Now imagine a large enterprise with 10,000 employees—this equates to 120,000 hours lost every single week, a staggering operational cost that many organizations fail to quantify.

But that’s just one of the problems siloed operations create.

The Problems Caused by Siloed Operations

Disconnected Teams and Processes

Many organizations struggle with fragmented workflows. IT, HR, finance, and operations often run on different platforms that don’t communicate. This lack of integration slows collaboration and limits efficiency. Bottlenecks go unnoticed, and businesses miss opportunities to respond quickly to market shifts. 

Example: Consider an enterprise launching a new product: if marketing operates on one system, sales on another, and production on a third, delays arise, miscommunication happens, and the go-to-market strategy falters.

Data Silos Limit Decision-Making

When key data is trapped in separate systems, decision-makers work with incomplete or outdated information. Leaders either rely on manual reporting or lack the visibility needed to align strategies. Hindering cross-department collaboration makes it harder for companies to leverage real-time insights. 

Example: A retailer struggling to optimize inventory may face stockouts in one location and excess stock in another, simply because inventory data is not synchronized across stores, warehouses, and suppliers.

Operational Inefficiencies

Legacy systems and disconnected processes force employees to waste time on repetitive, manual tasks. Instead of automating workflows, businesses lose productivity to unnecessary administrative work. 

Integration allows companies to streamline operations, eliminate redundant work, and reduce costs associated with inefficiencies. 

Example: Take a global manufacturer relying on email chains and spreadsheets to track procurement. A single missed update can result in delayed shipments, stalled production, and lost revenue.

Customer and Employee Experience Gaps

A lack of system integration affects both employees and customers. Employees struggle with cumbersome workflows that require constant switching between disconnected tools. Customers experience inconsistent service when teams lack access to real-time information. Cross-functional collaboration is essential for delivering seamless customer interactions. 

Example: Imagine a bank where a customer requests a loan, but their existing relationship with the bank—prior accounts, mortgage applications, or past inquiries—remains invisible to the loan officer. This lack of visibility frustrates the customer and slows down approvals.

Increased Security Risks

Fragmented security strategies make organizations more vulnerable to threats. Without a unified security framework, risks go undetected, and compliance efforts become inconsistent. MIT Sloan Review reports that more than 86% of audit and risk professionals believe that data silos weaken risk management efforts. 

Example: A healthcare organization handling patient data across multiple unlinked systems could face compliance violations if security gaps allow unauthorized access to sensitive records.

The Powerful Benefits of Intelligent Integration

Unified Systems Improve Efficiency

When organizations integrate their systems, they eliminate bottlenecks and improve operational agility. A centralized data platform ensures that teams have access to the same information, enabling faster decision-making. 

Example: A logistics company tracking shipments across a global supply chain gains real-time visibility into delays and can dynamically reroute deliveries to meet customer expectations. With AI, delays can be predicted and automatically avoided before customers are affected at all.

Automation Eliminates Manual Work

With integrated workflows, businesses can reduce reliance on repetitive manual processes. AI-powered automation speeds up critical operations and allows employees to focus on strategic work instead of administrative tasks. 

Example: A tech company using AI-driven contract review can cut legal review time from weeks to hours, accelerating deal closures.

Real-Time Data Enhances Decision-Making

Business intelligence tools provide up-to-the-minute insights across departments, ensuring leaders can make informed choices based on accurate, real-time data rather than static reports. 

Example: A retailer tracking in-store and e-commerce purchasing trends in real time can adjust promotions, optimize supply chains, and improve customer targeting. Agentic AI can potentially automate these processes with little or no human intervention.

Better Customer and Employee Experiences

Integrated systems improve both customer engagement and employee satisfaction. AI-powered platforms deliver personalized customer interactions, while user-friendly internal systems increase productivity and reduce frustration. 

Example: A telecom provider leveraging integration can equip customer service agents with full histories of prior interactions, allowing for faster resolutions and a more tailored support experience. AI integration can take this a step further by suggesting appropriate personalized solutions to customer issues instantly.

Scalability and Future-Proofing

As businesses grow, system integration ensures they can scale without introducing unnecessary complexity. Cloud-based architectures allow enterprises to expand efficiently without costly infrastructure overhauls. 

Example: A SaaS company entering new global markets can leverage cloud-based localization services and payment integrations to streamline expansion. LLMs are quickly becoming incredibly adept at these kinds of localization efforts.

The Technologies Powering Integration

Companies that successfully integrate their systems can fully leverage powerful tools designed to connect workflows, automate processes, and enhance collaboration.

  • Enterprise & IT Service Management – Atlassian and ServiceNow provide workflow automation and unify operations by seamlessly integrating IT with the rest of the organization.
  • AI-Powered Business Intelligence – Apptio and PowerBI offer unmatched visibility into data across all systems, enabling data-driven decision-making and real-time analytics.
  • Customer and Employee Experience Platforms – ServiceNow and Adobe enhance engagement through AI-powered personalization and predictive issue resolution.
  • DevOps and Agile Toolchains – Jira, GitHub, and Kubernetes streamline development and deployment with powerful automation and integrated workflows.
  • Cloud and Infrastructure Automation – AWS, Azure, and Google Cloud support flexible, cost-effective scaling that can be further enhanced with AI-powered technology and financial management capabilities.

A Strategic Approach to Intelligent Integration

Companies don’t need to overhaul their entire IT infrastructure at once. The most effective integration strategies take a phased approach:

  • Start with high-impact areas – Identify the most critical pain points and focus on integrating those first.
  • Secure stakeholder buy-in – Demonstrate early success to gain broader support across the organization.
  • Validate with pilot programs – Test and refine before scaling.
  • Expand integration strategically – Use data-driven insights to determine where additional integration efforts will drive the most value.

The Competitive Advantage of Integrated Systems

Businesses that connect their systems operate with greater speed, agility, and intelligence. They remove roadblocks, improve decision-making, and deliver better experiences for customers and employees alike.

Disconnected systems hold companies back. Integrated ones create new opportunities for efficiency, innovation, and sustained growth.

Sources:

Integrating Your Atlassian Cloud Ecosystem: Expert Insights for Maximizing Tool Synergy

Posted on May 21, 2024 by - Data, Integration & Governance, Platform Adoption & Governance

 

Atlassian ecosystem integrations FAQs addressed in this article:

  • What is the value of integrating the Atlassian ecosystem? – Integrating the Atlassian Cloud ecosystem enhances productivity, efficiency, and collaboration by leveraging AI and ensuring tools complement each other.
  • How does IT Service Management fit into the Atlassian ecosystem? – IT Service Management (ITSM) within the Atlassian ecosystem, particularly through Jira Service Management, streamlines incident, problem, and change management to align IT services with business needs.
  • Can non-IT teams benefit from Atlassian ecosystem integrations? – Yes, non-IT teams can utilize tools like Atlassian Jira Cloud (which will soon absorb all the functionality of the current Jira Work Management solution) for project management, risk tracking, and aligning with business objectives, enhancing team productivity and project clarity.
  • What role does enterprise agility play in the Atlassian ecosystem? – Enterprise agility, supported by tools like Jira Align, is crucial for adapting to market changes, aligning team efforts with business goals, and making informed decisions swiftly.
  • How can organizations optimize their Atlassian Cloud ecosystem? – Organizations can optimize their Atlassian ecosystem by consuming quality content for practical applications, leveraging live software demonstrations, and seeking expert assistance from Cprime for strategic tool integration.

 

The Atlassian suite is known for its robust set of tools designed to enhance productivity and collaboration. However, to truly harness the power of these tools, a strategic approach to integration is essential. This approach not only maximizes return on investment (ROI) but also significantly improves functionality, efficiency, and results across teams and projects.

The key to unlocking this potential lies in understanding and implementing best practices and strategies that maximize the use of the entire Atlassian Cloud ecosystem. Doing so effectively, businesses can create a seamless workflow that leverages the full spectrum of Atlassian tools, ensuring that every team member—both inside and outside IT—can contribute to the organization’s success in a meaningful way.

As we delve into the intricacies of creating an integrated tooling ecosystem, we’ll explore the transformative impact of artificial intelligence (AI), the importance of tool interaction and synchronization, and the critical areas of focus within the Atlassian suite. And, we’ll direct you to further resources that can aid your move to a better integrated Atlassian ecosystem.

Harnessing the Power of AI and Synergy in Atlassian’s Cloud Ecosystem

The synergy between different areas within the Atlassian ecosystem amplifies the benefits of a unified approach. When cloud-native tools such as Jira Software, Confluence, Jira Align, and others are seamlessly integrated, they create a cohesive environment that supports a wide range of business functions. This interconnectedness ensures that information flows freely between teams, enhancing collaboration, improving decision-making, and accelerating project timelines.

Moreover, a well-integrated tooling ecosystem facilitates a holistic view of projects and operations, allowing leaders to identify bottlenecks, allocate resources more effectively, and track progress in real-time. This comprehensive visibility is crucial for adapting to market changes swiftly and maintaining a competitive edge.

For modern enterprises, the value of leveraging artificial intelligence (AI) as they optimize their tooling ecosystem cannot be overstated. AI’s ability to analyze vast amounts of data, automate repetitive tasks, and provide actionable insights can significantly enhance the efficiency and effectiveness of the tools within the Atlassian suite. Some powerful AI features are already baked into many Atlassian Cloud tools, and additional AI functionality can be leveraged via strategic third-party integrations. 

Elevating Collaboration Through Strategic Tool Integration

One of the foundational best practices for tool integration is ensuring that tools not only interact but also complement each other. This approach allows for the seamless exchange of information and workflows across different platforms, eliminating silos and fostering a more collaborative and efficient work environment. 

For instance, integrating Jira Software with Confluence enables teams to link project tasks directly to relevant documentation, ensuring that all team members have access to the information they need, when they need it. And, integrating Bitbucket with Jira Software allows development teams to track the progress of code commits and pull requests directly within the context of their Jira tasks.

Moreover, the synchronization between tools can provide value across different levels of the organization. For example, integrating Jira Software with Jira Service Management ties together incident and change management with the development-level tasks needed to resolve the associated issues. And, tying together Jira Software and Jira Align opens incredible real-time monitoring and reporting capabilities, right up to the enterprise strategic level. This level of integration ensures that project managers and executive stakeholders have real-time visibility into the development process, facilitating better planning and decision-making.

Furthermore, the strategic integration of Atlassian Cloud tools can enhance the agility of an organization, enabling teams to respond more quickly to changes and opportunities. By automating workflows and creating a unified source of truth, teams can reduce the time spent on manual tasks—such as manually manipulating data or digging into another department’s tool looking for relevant information—and focus on delivering value to customers.

The strategic integration of Atlassian tools is a critical step towards building a more connected, efficient, and agile organization. By leveraging the strengths of each tool and ensuring they work together seamlessly, businesses can unlock new levels of productivity and innovation.

Navigating the Core Pillars of the Atlassian Cloud Ecosystem

While the suite of Atlassian tools cover a wide range of use cases and capabilities, there are three core functions we’ve found of most concern to our clients:

Transforming IT Service Management

At the core of efficient IT operations lies IT Service Management (ITSM), a discipline that has been significantly enhanced within the Atlassian ecosystem. ITSM’s role transcends traditional IT support, evolving into a strategic asset for aligning IT services with business needs. 

Within this ecosystem, Jira Service Management stands out by offering a versatile platform that streamlines incident, problem, and change management. This tool not only facilitates rapid response to IT issues but also fosters a proactive approach to minimizing future disruptions, thereby ensuring business continuity and enhancing customer satisfaction.

Empowering Teams Beyond IT

Beyond the realm of IT, the Atlassian Cloud suite offers robust solutions for work management, catering to the diverse needs of non-IT teams. 

Atlassian Jira Cloud (which will soon absorb all the functionality of the current Jira Work Management solution) emerges as a pivotal tool for project management, risk tracking, and aligning with overarching business objectives. This platform democratizes the power of project management, making it accessible to teams across the organization, from marketing to HR and finance. By providing a unified view of tasks, deadlines, and resources, Jira empowers teams to plan, execute, and track projects with unprecedented clarity and coordination.

Accelerating Enterprise Agility

Modern enterprises must be as nimble as small startups if they’re going to capitalize on the advantages of size and scope. The Atlassian ecosystem supports this agility through tools like Jira Align, which bridges the gap between strategic planning and execution. 

Jira Align serves as a strategic “hub” uniting the work being tracked and managed within Jira Software, JSM, and elsewhere, facilitating the alignment of team efforts with business goals, and ensuring that every task and project contributes to the broader objectives of the organization. This tool provides real-time insights into progress, dependencies, and outcomes, enabling leaders to make informed decisions and adapt strategies swiftly to meet evolving market demands.

Unlocking the Full Potential of Your Atlassian Ecosystem

To truly unlock the full potential of your Atlassian ecosystem, it’s essential to dive deeper into the practical applications and witness these tools in action.

We invite you to explore further by watching our webinar on demand, “Mastering an Integrated Atlassian Tooling Ecosystem: Strategies, Success Stories, and Best Practices”. This resource is packed with live software demonstrations that illustrate the transformative power of integrating Atlassian Cloud tools. Witness firsthand how Jira Service Management, Jira Work Management (now integrated into Jira Software), and Jira Align can be leveraged to streamline operations, enhance collaboration, and drive enterprise agility.

For organizations looking to optimize their Atlassian tooling ecosystem, Cprime stands ready to assist. Our expertise in Atlassian Cloud solutions can help you navigate the complexities of tool integration, ensuring that your business leverages the full suite of capabilities offered by the Atlassian ecosystem. Whether you’re seeking to enhance IT service management, empower non-IT teams with effective work management tools, or accelerate your enterprise agility, Cprime has the knowledge and experience to guide you towards achieving your goals.

Don’t let the potential of your Atlassian Cloud tools go untapped. Explore the webinar and more relevant content to gain valuable insights and strategies for mastering an integrated Atlassian tooling ecosystem. For personalized assistance and expert advice on optimizing your tooling ecosystem, contact Cprime today. Together, we can transform the way your organization works, making it more efficient, collaborative, and agile.

How to Use Allstacks to Measure and Improve Software Developer Productivity

Posted on February 15, 2024 by - Agile & DevOps, Data, Integration & Governance

Allstacks FAQs addressed in this article:

  • What is Allstacks? – Allstacks is a comprehensive solution designed to optimize performance and ensure timely delivery of projects by providing organizations with insights through performance metrics, KPIs, and SDLC insights.
  • Why is measuring developer productivity important? – Measuring developer productivity is crucial for organizations to achieve a competitive advantage, minimize risk, increase market share, and maximize ROI. It helps in making informed decisions based on the efficiency and effectiveness of development teams.
  • How does Allstacks measure developer productivity? – Allstacks measures developer productivity using a suite of tools that track performance metrics and KPIs, offer SDLC insights, and utilize frameworks like SPACE and DORA to provide a holistic view of productivity.
  • What are SPACE Metrics in Allstacks? – SPACE Metrics in Allstacks encompass Satisfaction and well-being, Performance, Activity, Communication and collaboration, and Efficiency and flow, offering a comprehensive framework to measure developer productivity beyond traditional metrics.
  • How does Allstacks help in aligning business goals with development efforts? – Allstacks helps in aligning business goals with development efforts through customizable KPI dashboards that focus on work contributing to the organization’s objectives, ensuring that development efforts are always aligned with strategic goals.
  • Can Allstacks integrate with existing tech stacks? – Yes, Allstacks can integrate with existing tech stacks through custom integrations development, ensuring seamless operation with project management software, version control systems, and other tools teams rely on.
  • What is the role of Cprime in leveraging Allstacks for organizations? – Cprime plays a crucial role in leveraging Allstacks for organizations by offering strategic discovery, customized implementation, coaching, training, and custom integrations development, transforming Allstacks from a tool into a catalyst for meaningful, data-driven change.
  • How does Allstacks facilitate real-time problem-solving? – Allstacks facilitates real-time problem-solving through customizable dashboards and real-time alerts for issues like increased response time and slowdowns in work patterns, enabling organizations to address problems before they escalate.
  • What are DORA Dashboards in Allstacks? – DORA Dashboards in Allstacks provide insights based on the DevOps Research and Assessment (DORA) metrics, offering a clear understanding of the effectiveness of development and operations processes.
  • How does Allstacks contribute to operational excellence? – Allstacks contributes to operational excellence by providing data-based strategies for measuring and improving developer productivity, enabling organizations to optimize their software development lifecycle and align technological projects with broader business goals.

With every company being a software company these days, the productivity of software developers has become a linchpin for organizations aiming to modernize their technology, embrace innovation, and secure a competitive edge. 

However, accurately measuring and enhancing developer productivity poses a significant challenge, often leaving decision-makers in the dark about the true efficiency and output of their development teams. This uncertainty can hinder strategic planning, risk minimization, market share expansion, and the maximization of return on investment (ROI), ultimately impacting an organization’s ability to future-proof its success.

Enter Cprime’s partnership with Allstacks, a game-changing solution designed to illuminate the path to operational excellence through data-based strategies. Allstacks offers a comprehensive suite of tools for tracking performance metrics, KPIs, and much more, providing the insights necessary to optimize performance and deliver projects on time. But integrating such a powerful tool into an organization’s workflow and reaping its full benefits requires a nuanced approach—one that Cprime is uniquely positioned to provide.

With a rich history of consulting, training, and tooling services focused on modernizing technology and adopting Agile methodologies, Cprime leverages Allstacks to transform businesses and elevate developer productivity to new heights. Utilizing a holistic solution encompassing strategic discovery, customized implementation, coaching, training, and even custom integrations development, we can ensure that our clients can harness the full potential of Allstacks without the need to coordinate multiple vendors.

But let’s not get ahead of ourselves. Why does developer productivity matter at all?

The Importance of Measuring Developer Productivity

There’s been some controversy about the topic, but we believe developer productivity stands as a critical metric (not existing in a vacuum, of course) that can significantly influence an organization’s ability to achieve a competitive advantage, minimize risk, increase market share, and maximize ROI. 

Yet, despite its importance, accurately measuring coder productivity remains a formidable challenge for many enterprises. Without a clear understanding of how efficiently and effectively their development teams are working, organizations risk making decisions based on incomplete or misleading information, potentially derailing their strategic objectives and innovation efforts.

What if you don’t measure developer productivity?

The consequences of not accurately measuring developer productivity are far-reaching. Projects may suffer from delays, cost overruns, and missed opportunities for innovation. Moreover, without concrete data to guide resource allocation and performance improvement initiatives, organizations may struggle to identify and address inefficiencies within their development processes. This lack of visibility can also hinder an organization’s ability to align its technological projects with broader business goals, ultimately impacting its competitive position in the market.

However, the challenge lies not just in measuring productivity but in doing so in a manner that is meaningful, actionable, and aligned with the organization’s strategic objectives. Traditional metrics, such as lines of code written or bugs fixed, fail to capture the complexity and nuance of modern software development practices. They overlook critical aspects such as collaboration, innovation, and the ability to adapt to changing requirements—factors that are essential for success in today’s dynamic business environment.

How to measure developer productivity right

Recognizing the need for a more comprehensive approach to measuring and improving developer productivity, Cprime has partnered with Allstacks to offer a solution that addresses these challenges head-on. 

Allstacks’ platform provides a suite of tools designed to track performance metrics and KPIs in a way that is both insightful and actionable, enabling organizations to make data-driven decisions that drive success. By leveraging Allstacks, companies can gain a deeper understanding of their software development lifecycle (SDLC), track progress using the framework of their choice, and optimize their operations based on solid, reliable data.

Introducing Allstacks: A Comprehensive Solution

In the landscape of software development and project management tools, Allstacks emerges as a beacon for organizations seeking to navigate the complexities of measuring and improving developer productivity. 

Allstacks is not just a tool; it’s a comprehensive solution designed to provide organizations with the insights needed to optimize performance and ensure timely delivery of projects. Its unique features and capabilities make it an indispensable asset for any enterprise looking to enhance its operational efficiency and align software development efforts with overarching business goals.

Key Features of Allstacks:

  • Performance Metrics and KPIs: Allstacks offers a robust suite of performance metrics and KPIs, presented in easy-to-read dashboards. These metrics provide a clear picture of where your team stands and the direction in which it’s headed, enabling you to make informed decisions about resource allocation, project prioritization, and process improvements.
  • SDLC Insights: Understanding your Software Development Life Cycle (SDLC) is crucial for identifying bottlenecks and areas for improvement. Allstacks allows you to track progress using the framework of your choice, whether it’s Agile, Waterfall, or something in between, giving you the flexibility to adapt the tool to your organization’s specific needs.
  • Automated OKR Tracking: Objectives and Key Results (OKRs) are vital for ensuring that your team’s efforts are aligned with your business objectives. Allstacks’ automated OKR tracking system simplifies the process of measuring your team’s progress against these objectives, facilitating a more strategic approach to project management and development.
  • SPACE Metrics: The SPACE framework offers a holistic view of developer productivity, encompassing Satisfaction and well-being, Performance, Activity, Communication and collaboration, and Efficiency and flow. Allstacks enables you to measure your team’s output against this comprehensive framework, providing insights that go beyond traditional productivity metrics.
  • DORA Dashboards: Understanding the core drivers behind your DevOps program is essential for optimizing your development and operations processes. Allstacks’ DORA dashboards offer a clear understanding of your effectiveness in these areas, based on the widely respected DevOps Research and Assessment (DORA) metrics.
  • Customizable Dashboards and Real-time Alerts: With Allstacks, you’re not just limited to pre-defined metrics and dashboards. The platform allows you to customize your dashboards and set up real-time alerts for issues like increased response time, lags in lifecycle, and slowdowns in work patterns. This level of customization and responsiveness ensures that you can identify and address problems before they escalate into delays.
  • Business Goal Alignment: Perhaps one of the most significant features of Allstacks is its ability to provide context for your team’s activities in relation to your business goals. Customizable KPI dashboards keep you focused on the work that matters most, ensuring that your development efforts are always contributing to the best possible outcomes for your organization.

Allstacks in Action

ShareFile saw a 32% reduction in cycle time and a 25% improvement in PR response time. 

At ShareFile, Allstacks served as both a driver for cultural transformation and necessitated a shift in culture to fully leverage its benefits. Allstacks introduced transparency, leading to a democratization of data, which in turn, fueled significant changes, including increased accountability. 

The implementation of Allstacks at ShareFile has proven effective in several ways. Notably, the company’s cycle time has seen a remarkable improvement of 32%, largely due to the engineering management’s enhanced visibility into ongoing work, allowing for necessary adjustments. ShareFile has also experienced a 25% reduction in pull request response time, indicating that the engineering teams and managers have a solid grasp of the workflow.

“As an engineering leader, you need to know what your teams are working on, what are their blockers, and how you can help. Allstacks gives us that.”

Now let’s see how Cprime’s expertise in operational excellence and data-based strategies can help your organization leverage Allstacks to its fullest potential, transforming the way you measure and improve developer productivity.

Pursuing Operational Excellence via Data-Based Strategies

Cprime stands at the intersection of innovation and practicality, offering a bridge between the potential of tools like Allstacks and the unique operational realities of each organization. Our expertise in operational excellence through data-based strategies is not just about implementing a tool; it’s about transforming the way businesses approach developer productivity and project management. Here’s how Cprime leverages Allstacks to bring about meaningful change:

Strategic Discovery and Customized Implementation:

At Cprime, we understand that each organization’s journey towards operational excellence is unique. That’s why our approach begins with a strategic discovery phase, where we dive deep into your current processes, challenges, and objectives. This understanding allows us to tailor the implementation of Allstacks to your specific needs, ensuring that the solution not only fits seamlessly into your existing tech stack but also addresses your most pressing challenges.

Custom Integrations Development:

Cprime goes beyond the standard capabilities of Allstacks by offering custom integrations development. This service ensures that Allstacks works in harmony with your existing tech stack, pulling in data from various sources and providing a more comprehensive view of your team’s performance. Whether it’s integrating with your project management software, version control systems, or any other tools your team relies on, Cprime makes it happen.

In essence, Cprime’s expertise transforms Allstacks from a powerful tool into a catalyst for meaningful, data-driven change within your organization. By partnering with Cprime, you gain more than just access to Allstacks; you gain a partner committed to helping you achieve your strategic objectives and enhance your operational efficiency.

Coaching and Training for Maximum Adoption:

Adopting a new tool can be a daunting task for any team, but with Cprime’s coaching and training programs, it doesn’t have to be. Our customized training is developed based on your unique circumstances and focuses on promoting internal adoption of Allstacks. We teach users how to integrate the tool into their daily workflows effectively, how to interpret and act on the data provided, and how to set up optimal metrics sets to reach your business goals. This hands-on approach ensures that your team is not just using Allstacks but is getting the most benefit from it.

Ongoing Support and Coaching:

Cprime’s commitment to our clients doesn’t end with the initial training sessions. We offer ongoing support and coaching to address any challenges that arise as teams deepen their use of Allstacks. This continuous engagement ensures that clients can adapt and evolve their use of Allstacks as their projects, teams, and business objectives change over time. 

Are You Ready to Start Maximizing Your Data-Driven Decision Making?

The journey towards operational excellence and enhanced developer productivity is not a solo endeavor. It requires a partner who understands the unique challenges and opportunities of your organization, and who can guide you in harnessing the power of tools like Allstacks to achieve your strategic objectives. 

Cprime is that partner. 

With our deep expertise in consulting, training, and tooling services, we are committed to helping you navigate the complexities of modern software development and unlock the full potential of your team.

Looking ahead, the importance of measuring and improving developer productivity will only continue to grow. Organizations that embrace this challenge, armed with the right tools and the right partners, will be the ones that lead the way in innovation, efficiency, and success. We invite you to join us on this journey.

If you’re ready to transform your approach to developer productivity and operational excellence, we encourage you to contact an Allstacks expert at Cprime. Together, let’s build a future where your organization not only meets the challenges of today but thrives in the opportunities of tomorrow.

The Pragmatic Agile Coach’s Approach to Product Thinking and Portfolio Governance

Posted on August 1, 2023 by - Agile & DevOps, Data, Integration & Governance

When does a transformation often hit the wall as it looks to make additional progress within an organization that’s seemingly eager to embrace Agile ideals and principals? Look no further than the Program Governance Board.

The Governance Board

Depending on your organization, this board may have different names—a Steering Committee, Oversight Committee or even Board of Directors. Whatever its title, the Governance Board is made up of executive-level stakeholders with strategic insight into the company’s goals and objectives, technical knowledge, functional responsibilities, operational accountability, portfolio management responsibility, and the ability to represent important stakeholder groups. 

In traditional organizations, funding for projects may be via a single source or through multiple Portfolios. The governance of the project will vary to meet the needs of the stakeholders in the project and the lifecycle chosen.

In this way of thinking, all projects require funding in some way. In most situations, money needs to be provided to implement the project. It is the business case that provides the justification for this funding and the Governance Board doles out the money.

My mind always goes to the smoke-filled rooms of the past. With the Governance Board making decisions, in most cases, it is not based on empirical data, but instead heavily influenced by the pervasive organizational culture. If the culture is conservative and risk averse, they allocate funds with an eye dropper. If the organization has an “old boys” network, bargaining goes on – “I’ll give you the money for the infrastructure upgrades you want, if you give me what I need to implement the new CRM tool.”

What is often a detrimental part of this process is the way it denigrates the teams which are the cornerstone of any IT organization by making them “grovel” for funds each year; and more significantly, the colossal waste of time that comes from all parts of the organization having to annually “justify their existence.”

When is a Product a Product?

Make a Wish was an American children’s television series which ran in the 1970s. In it, the host would introduce a word and discuss the many various meanings it might have. “What is a ball? A ball can be something you toss to a friend. A ball could be a dance Cinderella attended. You could ‘have a ball’ meaning a good time. Or a ball could be a type of jar.” As a young child, I remember being utterly confused by the end of the segment and wondering, “so what the heck is a ball?”

The same is true when we as Agile Coaches introduce “Product Thinking”. Exactly what is the Product we are managing? If we are working with a bank, a product could be the “Everyday Checking” product they offer to their customers. A product could be the AI-based loan qualification system. A Product could be the Financial Advisor services they offer as an additional revenue stream.

Weeding through the confusion

My mentor in all things Product Agility, Anne Steiner sums it up this way:

“Product Agility is having that ability to get common alignment with what we’re building, why we’re building, who we’re building it for, and then bringing that all the way through that process: shortening those delivery cycles so that we can learn faster by having real code in the market real validation of our assumptions, and then adjusting. Product Agility is unlocking a company’s ability to learn to maneuver and pivot.”

I have had success framing the discussion of Product in this way:

A Product:

  • satisfies a business need
  • delivers value to the stakeholders (internal or external)
  • has a clear boundary and customers
  • achieves some measurable value

These examples might help to provide leaders with a pragmatic way of thinking of their products:

Consumer Products:
Products which satisfy the needs of an end customer		 Business Products:
Products which satisfy the needs of internal customers (generally called Businesses)		 Services as a Product:
A product could be a service
An Electric Bicycle HR Management system for employees who manufacture the bicycles Coordinated service arrangements for repairs under warranty
Chocolate Chip Cookies ERP system for managing the supply chain of raw material and finished cookies An automated baking process
Commercial Flags CRM system for managing the leads and prospects for flag sales Delivery of the flag to the customer

The next step in having leaders from both the Agile transformation and traditional PMO move forward with a more flexible funding approach is finding a way to help them comprehend how the two seemingly disconnected concepts of Project Funding and Product Agility are intertwined.

The example of the “Website Project”

Something virtually every organization can quickly wrap their head around is their web presence on the Internet. They all will have a website which ‌serves multiple purposes. It falls squarely into the Business Products category we defined for Product Agility. The benefits the website provides will be readily known to these leaders and easily understood:

  1. Create a global presence 
  2. Act as a point of contact 
  3. Sell products
  4. Share the latest news 
  5. Learn about customers
  6. Market your organization to potential employees 

So, if we agree the website should be treated as a Product, we can then move into the more challenging cultural shift of how we budget for the work. 

In a traditional Governance Board model, we would be required to go into that “smoke-filled room” with our funding requirements for the following year. We may be expected to provide any or all of the following:

  • Project Plan
  • Business Case
  • Project Schedule
  • Risk Register
  • Scope Statement
  • Project Budget
  • Business Requirements Document (BRD)
  • Resource / Capacity Plan
  • Project Proposal
  • Project Brief

All of this to justify the existence of a team (or group of teams) who is already acknowledged as providing a technical solution which is integral to the organization. The Project Packet with the aforementioned documents is taken to the Governance Board looking for a Go / No-Go decision.

Is it really in the realm of possibilities that the Website Product will not be funded?

There is a better way—Lean Portfolio Management

In our example, Leadership may come to acknowledge that traditional methods of portfolio management are not aligned with the needs of their Agile website product. An alternative approach is to adopt Lean Portfolio Management practices. Lean Portfolio Management (LPM) describes how senior leadership applies lean principles to connect strategy to execution. Portfolio management teams learn about an enterprise’s strategy and allocate a budget towards the execution of that strategy.

Like any portfolio, an LPM portfolio of investments is creatively determined and actively managed across the investment life cycle. The primary emphasis of LPM is to align Agile development with business strategy, with a focus on driving the delivery of value to customers through the creation of products and solutions. Combining LPM with Agile development practices offers a path to improving business agility.

While traditional Project Portfolio Management focuses on creating a set of tightly structured project plans and building short-lived teams to execute those plans, LPM focuses on:

  • Bringing loosely structured value opportunities to long-standing teams-of-teams
  • Asking teams to define the needed work
  • Monitoring emerging solutions to iterate toward market fit

One of the biggest benefits of moving to a value-based funding model (in our example based on the value the website returns to the organization) is that much of the decision making is pushed down the organizational structure to the team themselves. Your development team has the information to make the best decisions. 

Additionally, value-based funding improves the quality and working environment of your teams. For example, projects often start and stop, and teams get reallocated. But with this value-based product-centric approach, you maintain the same knowledge on the same team and keep development flowing continually. You also eliminate the demoralizing exercise of “justifying one’s existence”. This gives your developers deep subject matter knowledge on their software and lets teams build a natural rhythm based on working with one another over an extended period, thus improving their productivity.

When a budget overrun happens in a project, it can cause major development delays while the entire project is recalibrated. Setting annual budget boundaries for the team, aligned to the value they provide, helps to eliminate such delays.

Achieving an outcome where a traditional organization embraces the concepts of Product Agility and Lean Portfolio Management is no small feat. It will require patience and the ability to “sell” leadership on the value these changes will bring to their organization. But as LPM becomes more pervasive in the marketplace of ideas, it will allow Coaches to focus leaders on the benefits of keeping development teams aligned and working uninterrupted, maintaining an openness to change and empowering development teams while keeping the focus on bringing the greatest amount of business value to your organization.

If you’d like to dive deeper into a solution to the portfolio management conundrum, consider our white paper, “Getting Started with Portfolio Management” or our webinar, “How to Get Started With Lean Portfolio Management”.

Data Integration Techniques—Which Should You Use?

Posted on May 4, 2023 by - Data, Integration & Governance

Today’s business is built around data and the algorithms that process it to extract the maximum value. The average company also uses dozens of apps and filing systems to generate, analyze, and store that data, often making it hard to gain value from it. Data integration merges the data from disparate systems, enabling a full view of all the information flowing through an organization and revealing a wealth of valuable business insights.

What is Data Integration?

Data integration is the process of combining data from various sources into one unified view for efficient data management in order to derive meaningful insights and gain actionable intelligence.

In a business tech environment made up of thousands of apps and platforms, data integration techniques and tools aim to aggregate data regardless of its type, structure, or volume. It is an integral part of a data pipeline, encompassing data ingestion, data processing, transformation, and storage for easy retrieval.

Benefits of Data Integration and Why We Need it

Companies gather enormous volumes of data from various sources. For data to be meaningful, it must be accessible for analysis. Yet fresh data enters the organization every second, in multiple formats, and is stored in various locations.

Without unified data, a single report typically involves logging into multiple accounts on multiple sites, accessing data within native apps, copying the data, reformatting, and cleansing, all before analysis can happen.

The solution—data integration—offers a number of advantages:

  • Improves collaboration – Employees in various departments and locations need access to the company’s data for shared and individual projects. And, they’re generating their own data all the time. Data integration allows self-service access to the company’s data across all lines of business, often in real-time, automatically.
  • Saves time and boosts efficiency – Automated data integration techniques cut down significantly on the time required to prepare and analyze that data, reducing or eliminating manual data collection. And, it saves the dev team from having to regularly create new ad hoc integration tools for one-off analyses.
  • Reduces errors and rework – Anytime you remove manual effort from the equation, error rates go down. Flawed analysis based on simple human error in the data collection or translation process can cost both time and money. With automatically synchronized data, these issues are all but eliminated.
  • Improved visibility in real-time – In many cases, data integration can remove the need to re-run reports as data changes, since automated reports and dashboards will continually update in real-time once the integration is established.

Key Data Integration Use Cases

Let’s focus on the four primary use cases that require various data integration techniques:

  • Data ingestion
  • Data replication
  • Data warehouse automation
  • Big data integration

Data Ingestion

The data ingestion process involves moving data from a variety of sources to a storage location such as a data warehouse or data lake. Ingestion can be streamed in real time or in batches and typically includes cleaning and standardizing the data to be ready for a data analytics tool. Examples of data ingestion include migrating your data to the cloud or building a data warehouse, data lake, or data lake house.

Data Replication

In the data replication process, data is copied and moved from one system to another—for example, from a database in the data center to a data warehouse in the cloud. This ensures that the correct information is backed-up and synchronized to operational uses. Replication can occur in bulk, in batches on a scheduled basis, or in real time across data centers and/or the cloud.

Data Warehouse Automation

The data warehouse automation process accelerates the availability of analytics-ready data by automating the data warehouse lifecycle—from data modeling and real-time ingestion to data marts and governance.

Big Data Integration

Moving and managing the massive volume, variety, and velocity of big data requires advanced tools and techniques. Your big data integration system needs intelligent big data pipelines that can automatically move, consolidate, and transform big data from multiple data sources while maintaining lineage. It must have high scalability, performance, profiling, and data quality capabilities to handle real-time, continuously streaming data.

Data Integration Techniques

There are five different approaches, or patterns, to execute data integration:

  • ETL (Extract, Transform, and Load)
  • ELT (Extract, Load, and Transform)
  • Data streaming
  • Application integration via API (Application programming interface)
  • Data virtualization

To implement these data integration techniques, data engineers, architects and developers can either manually code an architecture using Structured Query Language (SQL), or more often, they set up and manage data integration tools, which streamline development and automate the system.

ETL (Extract, Transform, and Load)

An ETL pipeline is a traditional type of data pipeline which converts raw data to match the target system via three steps: extract, transform and load. Data is transformed in a staging area before it is loaded into the target repository (typically a data warehouse). This allows for fast and accurate data analysis in the target system and is most appropriate for small datasets which require complex transformations. For example, the data consolidation approach for cloud data integration is based on ETL technology. 

ELT (Extract, Load, and Transform)

In the more modern ELT pipeline, the data is loaded immediately and then transformed within the target system, typically a cloud-based data lake or data warehouse. This approach is more appropriate when datasets are large and timeliness is important, since loading is often quicker. ELT operates either on a micro-batch or change data capture (CDC) timescale. Micro-batch, or “delta load,” only loads the data modified since the last successful load. CDC continually loads data as and when it changes on the source.

Data Streaming

Instead of loading data into a new repository in batches, streaming data integration moves data continuously in real-time from source to target. Modern data integration (DI) platforms can deliver analytics-ready data into streaming and cloud platforms, data warehouses, and data lakes.

Application integration via API (Application programming interface)

Application integration through an API allows separate applications to work together by moving and syncing data between them. This can support operational needs, such as ensuring that your HR system has the same data as your finance system. Since various applications usually have unique APIs for giving and taking data, Software as a Service (SaaS) application automation tools like Workato can help you create and maintain native API integrations efficiently and at scale.

Data Virtualization

Like streaming, data virtualization also delivers data in real time by virtually combining data from different systems, but only on demand. Virtualization and streaming are well suited for transactional systems built for high performance queries.

Challenges of Data Integration

Taking several data sources and turning them into a unified whole within a single structure is a technical challenge unto itself. Here are some common challenges that organizations face in building their data integration platform:

  1. How to get to the finish line — Anyone implementing data integration must understand what types of data need to be collected and analyzed, where that data comes from, the systems that will use the data, what types of analysis will be conducted and how frequently data and reports will need to be updated. This can be an overwhelming task for most IT teams.
  2. Data from legacy systems — Integration efforts may need to include data stored in legacy systems. That data, however, is often missing markers such as times and dates for activities, which more modern systems commonly include, making integration very difficult.
  3. Data from newer business demands — New systems today are generating different data (such as unstructured or real-time) from many sources such as videos, IoT devices, sensors, and cloud. Adapting your infrastructure to integrate all this data is critical, but it’s extremely difficult as the volume, the speed, and the new format of data all pose new challenges.
  4. External data — Data taken in from external sources may not arrive at the same level of detail as internal sources, making it difficult to examine with the same rigor. Also, contracts in place with external vendors may make it difficult to share data across the organization.
  5. Keeping up — Once a data integration platform is up and running, the task isn’t done. The data team must keep the data integration service on par with best practices, as well as the latest demands from the organization and regulatory agencies.

Data Integration Tools

Agile_Facilitation_Medium_black_coralData integration tools and techniques are available across a broad range of organizational levels, from fully automated to manual methods. Typical tools and techniques for data integration include:

  • Manual Integration or Common User Interface: There is no unified view of the data. Users operate with all relevant information, accessing all the source systems.
  • Application Based Integration: Requires each application to implement all the integration efforts; manageable with a small number of applications.
  • Middleware Data Integration: Transfers integration logic from an application to a new middleware layer.
  • Uniform Data Access: Leaves data in the source systems and provides  a unified view to users across the enterprise.
  • Common Data Storage or Physical Data Integration: Creates a new system for storing a copy of the data from the source system, which is managed independently.

Developers may use SQL to code a data integration system by hand. There are also data integration toolkits available from various IT vendors that streamline, automate, and document the development process.

The optimal data integration tool will:

  1. Support flexible pipelines
  2. Provide numerous integrations
  3. Include a built-in job scheduler
  4. Include job triggers
  5. Provide an intuitive interface

Data integration allows you to analyze and act upon a reliable, single source of up-to-date data you can trust. This allows analysts, data scientists and businesspeople to use BI and analytics tools to identify patterns and produce actionable insights that improve performance and help you compete.

The best way to get an ideal data integration strategy is to have a trusted professional partner. Contact Cprime specialists to get professional help and see what insights your data can deliver.

Gitlab Integrations: Popular Synchronization to Simplify Software Development

Posted on April 13, 2023 by - Data, Integration & Governance

GitLab integrations make collaboration more convenient and productive. Working on a project often requires the use of several tools and applications for different aspects of the workflow. But jumping from one tab to another is frustrating and an opportunity to miss important information. That’s why the goal of GitLab integrations is to connect the tools enterprise teams use and simplify how they collaborate.

What is GitLab?

GitLab is a web-based git repository that provides open and private repositories, issue-following capabilities, and wikis. It is a complete DevOps platform that enables professionals to perform all the tasks in a project—from project planning and source code management to monitoring and security. It allows teams to collaborate and build better software.

GitLab helps teams reduce product lifecycles and increase productivity, which ‌creates value for customers. The application doesn’t require users to manage authorizations for each tool. Once permissions are set, everyone in the organization has access to every component.

Fast and easy GitLab integrations: What are they for?

GitLab offers a wide assortment of plugins and integrations, allowing you to extend and enhance its already impressive functionality. These integrations leverage the overall functionality of the ecosystem and improve the development workflow, making the development team’s work easier and faster.

Using GitLab integrations can help you meet commitments and compliance requirements more easily, while reducing your reliance on manual communication to update cross-functional teams.

Top 10 popular GitLab integrations

  1. GitLab Jira Integration
  2. GitLab Slack Integration
  3. GitLab Jenkins Integration
  4. GitLab Teams Integration
  5. GitLab GitHub Integration
  6. GitLab SonarQube Integration
  7. GitLab Trello Integration
  8. GitLab Asana Integration
  9. GitLab Confluence Integration
  10. GitLab Snyk Integration

GitLab Jira integration

Jira is a software application by Atlassian used for issue tracking and project management. Thousands of Agile development teams use the tool to track bugs, stories, epics, and more. It is a perfect tool for teams to create, track, and prioritize tasks. Originally designed as a bug and issue tracker, Jira has evolved to manage software development, Agile project management, bug tracking, scrum management, content management, marketing, professional service management and so much more.

The Jira GitLab integration lets your development team follow the progress of issues through the continuous integration/continuous delivery (CI/CD) process without leaving Jira. Meanwhile, DevOps practitioners receive real-time updates on Jira issues without leaving GitLab. These features can save time and effort while improving transparency across the development, testing, and deployment workflow.

But, for many organizations, several beneficial features are lacking in the native GitLab integration with Jira because every business is unique, and out-of-the-box tools may not meet every need. Sometimes a custom Jira GitLab integration is a better fit.

GitLab Slack integration

Slack is a messaging program designed to help team members work more efficiently by allowing them to communicate, collaborate, share files, and assign tasks.

With a GitLab Slack integrations, the team can automatically receive real-time updates in Slack whenever something changes in your GitLab repositories. This keeps your team up to date with what is happening with GitLab and proposed coding changes. You can also issue a command in Slack that takes effect in GitLab.

GitLab Jenkins integration

Jenkins is an open-source software development platform enriched with continuous integration (CI) and other DevOps automation capabilities. Organizations use Jenkins to build and deploy applications and integrate with GitLab or other DevOps tools.

A Jenkins GitLab integration allows you to build and deploy an application on Jenkins and reflect the output on the GitLab user interface more conveniently. Combining these tools lets you trigger a Jenkins build when the team pushes code to a repository or creates a merge request.

For example, you may implement a GitLab Jenkins integration if you intend to migrate your CI from Jenkins to GitLab CI/CD in the future. Or you may need a temporary solution when you invest in Jenkins Plugins and continue using Jenkins to create your apps.

GitLab Teams integration

Microsoft Teams is a popular Slack alternative—a hub for teamwork, productivity, and collaboration. It brings together your chat, meetings, notes, people, and tools in one place.

A Teams GitLab integration displays notifications about GitLab projects in Microsoft Teams to keep the team informed and engaged. It is easy to implement and helps workflows run smoothly, triggering workflows automatically as updates occur.

With GitLab Microsoft Teams integrations you can automate redundant manual tasks and save precious time and effort, orchestrate your business process by integrating the apps you use efficiently, and move data seamlessly.

GitLab GitHub integration

Both GitHub and GitLab are great ways to host your git repositories online. Both offer powerful tools to manage your open source or private code projects.

The major difference between GitHub and GitLab is the platform each presents. GitHub has higher availability and is more focused on infrastructure performance, while GitLab is more focused on offering a features-based system with a centralized, integrated platform for web developers.

So why choose if there is a GitLab and GitHub integration?

  • GitHub repository import makes importing a repository from GitHub super easy.
  • Repository synchronization from Gitlab to Github allows your team to use GitLab as the principal source of information but maintain a GitHub repository. Team members can use GitHub’s issue tracker, wiki, and forum.

GitLab SonarQube integration

We divide code review into two types: manual and automatic review. While an individual tester—a developer or engineer, usually—does manual review, tools or programs perform automatic review. Developers can use a few tools for automatic review, and one of the most popular is SonarQube.

A SonarQube GitLab integration allows you to maintain code quality and security in your GitLab projects. If you integrate GitLab with SonarQube, you can:

  • Sign in to SonarQube with your GitLab credentials.
  • Import your GitLab Projects into SonarQube to set up SonarQube projects easily.
  • Integrate analysis into your build pipeline.
  • See your Quality Gate and code results right in GitLab so you know if it’s safe to merge your changes.

GitLab Trello integration

There is a wide range of project management tools available in the market that can simplify the work management process, but Trello stands out among the rest as it offers a straightforward and intuitive approach to organizing and keeping track of all your projects at a glance.

Sometimes a large project might require multiple team members to work simultaneously, and in this case, it’s challenging to keep track of everyone’s contributions to the project. Luckily, GitLab can solve this problem by enabling multiple individuals to work on a single project simultaneously. With the two of these needs coinciding, a Trello GitLab Integration makes sense.

Integrate Trello with GitLab to maximize the output of any project team.

GitLab Asana integration

Asana is a project management tool that helps individuals and businesses manage projects, create and track tasks, assign responsibility, and set timelines.

With an Asana GitLab integration, your work can easily flow across tools and teams. In addition, the integration allows you to sync tasks, issues, projects, Asana custom fields, GitLab labels, comments, assignees, and more to stay on top of your projects and promote collaboration.

Project managers rarely deal with developer platforms, whereas software development teams would rather focus on DevOps than project management tools. The Asana GitLab integration may solve this problem for organizations by syncing both teams seamlessly and automatically. GitLab would instantly reflect any changes or updates made on Asana by the project managers for the developers to take action or note.

GitLab Confluence integration

Confluence is another exceptional supporting tool for developer teams. It is ideally suited for project management, offering an essential single source of truth for developer teams. The platform makes it easy to maintain online documentation, collaborate on content, assign tasks to team members, and manage crucial project deadlines and milestones.

A GitLab Confluence integration simply means linking both platforms so information flows freely from one platform to the other. An action in one medium can automatically trigger a predetermined action on another platform. That way, you don’t have to enter information in both GitLab and Confluence manually.

GitLab Snyk integration

Snyk is an open source security platform for finding vulnerabilities in the source code of an application. It further provides the severity of vulnerabilities, classifying them as major, minor, or critical, so you can prioritize and take suitable action.

Snyk integrates with developer tools and workflows to continuously find and automatically fix vulnerabilities, so you can ensure security at scale without affecting velocity. A Snyk GitLab integration is helpful to create intelligent security bots which can efficiently create secure environments for future deployments.

The GitLab Snyk integration can help you:

  1. See Snyk tests that check for vulnerabilities in your pull requests.
  2. Get alerts with fixes when new vulnerabilities are disclosed.
  3. Get alerts if a new upgrade is available for a vulnerability that affects you.

Our case

About 70 percent of digital transformations fail because of complexity, bottlenecks and inefficient use of management tools. Businesses that require custom GitLab integration might struggle with the transformation process, but there are a few common issues.

Cprime brought together GitLab and Jira in a custom integration solution for one of our clients to speed up the software delivery process and meet organizational business objectives faster. As a result, the unique integration allowed the client to:

  • Access Jira Board View inside GitLab to keep them from jumping around
  • Pass Build information from GitLab to Jira
  • Display GitLab Deployment info inside Jira
  • Create Jira Issues from unresolved merge request threads
  • Create Jira Issues from GitLab
  • Create a GitLab branch from a Jira Issue
  • Display feature flag info
  • Add comment integrations

Cprime is ready to help you build a custom GitLab solution to get the most out of your tooling stack. If you are ready to integrate your business tools with GitLab in a custom solution, or your out-of-the-box solution needs to be fine-tuned, speak to an integration expert today.

Data Integration Strategy: Designing a Future for Your Business

Posted on February 24, 2023 by - Data, Integration & Governance

A data integration strategy involves taking a comprehensive look at the data used in your organization and the integration use cases and pain points you need to address, and then developing the best solution for integrating data across platforms and applications.

With all those factors, it’s hard to know where to begin. So, let’s start at the beginning.

What is a Data Integration Strategy?

A data integration strategy identifies what you need to do to achieve your data integration goals.

Based on the strategy developed, you can form a detailed plan to achieve your strategic outcomes. The plan will include what needs to be done, who does it, and when. It also identifies who is accountable for managing it.

All data integration strategies should align with the organization’s business goals and:

  • Consider your data use cases and pain points
  • Examine data types
  • Consider the project budget
  • Guide you to a wise, practical, and consistent integration approach
  • Enable a solution flexible enough to adapt to changing future needs

Ideally, your integration approach should help you achieve business goals, enable easy data access, and connect the data sources the business needs to be efficient, innovative, adaptable and profitable.

How to Set Long-term Goals for a Data Integration Strategy Within an Organization

Having a long-term view is an essential part of choosing the right enterprise data integration option. If you only focus on your current requirements and infrastructure, then you may need to change your integration processes and solutions in a few years. When you go through the factors in the previous section, think about where your organization may be in the next one, five, or ten years. Some data integration options are better suited to supporting your organization’s long-term needs than others, and you can implement those now rather than needing to switch in the future.

The 10 Main Elements of a Data Integration Strategy Process:

There are ten core elements to keep in mind when developing your master plan. If you don’t consider these elements when you’re putting together a strategy, you may not get the most value out of your data integration projects.

1. Scalability

The amount of data being generated today is mind-boggling compared to just a few years ago, and the rate is only accelerating. Your organization’s workload may change significantly over the next five to ten years. Your data integration strategy requires a scalable approach that’s prepared to handle the data loads of the future and today. One way to handle scaling is to connect it to real-time events and automate resource allocation based on your integration activities.

2. Anytime, Anywhere Access

The rapid adoption of remote work policies because of the 2020 pandemic has further driven the need to create highly accessible data integration resources. Ad hoc data requests, routine integration, and countless other use cases may occur with remote employees, those on business trips, field workers, and other stakeholders outside the physical business location.

You need to consider how you will support remote access, from infrastructure to security and beyond. The user experience should be seamless from both sides of the connection. Your work-from-home staff may need upgrades to their home office equipment as part of this plan so you avoid accessibility pitfalls associated with insufficient Internet speeds, unsecured home networks, and obsolete hardware.

3. Interoperability with Enterprise Solutions

You won’t get far with a data integration strategy that doesn’t account for the enterprise solutions you have in place. Consider:

  • Where your data is coming from and going to
  • The storage options you currently use
  • New types of data storage
  • The application programming interfaces (APIs) you can leverage.

Your strategy should move you closer to creating a silo-free enterprise environment that supports massive data movement and transformation.

4. Adaptable Framework

  • How agile is your data integration?
  • Is it future-proofed to:
    • Help drive the adoption of new technologies
    • Work with alternative data sources, APIs, and formats
    • Adapt to an ever-changing enterprise environment?

An agile data integration strategy uses a framework that can accommodate new technology without a massive expenditure of resources. You can quickly bring in new solutions ahead of the competition and reduce the development workload required to make it work.

5. Where is Your Infrastructure

Many applications and solutions are moving to the cloud or are developed with a cloud-native approach. But on-premises infrastructure also has its strengths in the enterprise.

Accommodate the full range of deployment options to avoid limiting your options in the future. You can decide based on what’s best for a particular solution, rather than trying to force it into an on-premise or cloud data integration strategy.

6. Data Types and User Access

  • What data types and sources are you working with?
  • Do you need to integrate these or just certain ones?
  • Are there data types that you’re likely to work with in the future that are not currently in use in your organization?

By defining exactly what data needs integration, you can avoid choosing solutions that present challenges when working with certain formats or that can’t support future requirements.

  1. The easiest way to address this is to conduct a data audit. You may discover data types that were not accounted for and some that may need to be replaced.
  2. The next step is to understand who needs access to the data. Most users only need access to a small portion of your enterprise’s data, and controlling that access is critical from a security standpoint.

7. Regulatory Compliance

Data regulations continue to develop and falling out of compliance can be costly. Data management and privacy are top-of-mind for many stakeholders, and adapting to sweeping changes after the fact can lead to significant development costs and business disruption.

Granular control over the data integration strategy helps your enterprise adapt to new regulations and current requirements. You may already cover future compliance through your data governance policies, but revisiting it allows you to address challenges unique to data integration.

8. Data Security

How do you protect data that is being pulled from multiple sources and variably transformed‌? Data breaches and losses are another costly concern for enterprises, but you can manage your risks with the right strategy.

The typical type of attack for your industry, the type of data that you need to protect, and the regulations you must follow all inform the method for data security during integration. Some common vulnerabilities include

  • Attack opportunities as data moves from one solution to the other
  • Internal malicious actors
  • Phishing
  • Social engineering

A proactive, multi-layered security approach can get ahead of existing and emerging threats.

9. Available Resources and Talent

Implementing a data integration strategy requires access to sufficient resources and specialists. Think about the support you need to deploy data integration across your organization successfully, and how to drive adoption.

You may need a combination of in-house and outsourced staff to handle key parts of data integration, such as

  • The initial development and deployment
  • Removing data silos from your organization via strong change management plan so stakeholders understand what the strategy means for them and how they can benefit from it
  • End-user training and ongoing feedback from stakeholders to shape the data integration solutions you use

10. Business Value

  • Exactly how does your organization benefit from a large-scale data integration strategy?
  • What results are you hoping to see after a solution is in place?

Identify key metrics, and how they affect the organization positively to increase support for your strategy. You can point out:

  • Greater efficiency and productivity
  • Improved visibility into the organization’s data
  • Potential bottom-line impacts that come from data integration.

The Benefits of a Data Integration Strategy

clipboard icon

Gets stakeholders on the same page:

  • What are everyone’s goals with this project?
  • What challenges do they want to solve through data integration?
  • What is the process scope?

When you create a comprehensive strategy, you answer these questions and leave nothing to the imagination.

Better informs the tool and software selection process:

Your data integration strategy requirements influence the software or platform that best suits these needs. If you don’t have a strategy in place, then you could run into a solution mismatch that costs significant time and resources to fix.

Addresses current and future data integration challenges:

You identify problems that stand in the way of data integration in your organization and what you need to change in order to solve them.

Reduces wasted resources:

Your strategy provides a blueprint for data integration and cuts down on resources that could be wasted because of inefficiencies in this process.

Opens up communication channels between affected departments:

An enterprise-wide data integration process should have input from stakeholders outside of the integration team. You can discover new unknown use cases, solutions that need support, and data formats.

Creates a security-centric foundation for data integration:

Consider the security challenges that this process introduces, and how to mitigate the risks that exist to keep your data safe when it moves between solutions through the data integration tool.

Identifies potential data integration pain points:

Talk with end-users throughout the organization to discover the data they would like to access, where they need the most support, and the limitations of their current software. Then incorporate solutions into your strategy.

Empowers organizations to become data driven:

When you improve access to data throughout the organization, you also boost its visibility. Ad hoc data requests and real-time updates can go a long way to influencing business decisions.

Removes data silos in the organization:

When employees can access data across teams and business units, it promotes seamless collaboration between departments.

Maximize the value of your data:

You can use the data in many solutions and use cases, which allows you to get more out of it.

Improves data management:

A comprehensive data integration strategy has many provisions in place for controlling how data moves throughout the organization. So, as new goals, solutions, sources, or requirements arise, managing the change will be easier.

Final thoughts

From the initial development and deployment of new data systems to the need for a change management plan, end-user training, and ongoing feedback, successful data integrations involve many moving parts. A good data integration strategy will consider many other issues not explored here, such as data security, regulatory compliance, and the availability of resources.

Many organizations have decided that relying on an experienced integration partner can simplify and improve the process. Cprime’s skilled IT specialists can help you create and implement a unique strategy for your enterprise.

Explore further with our popular webinar, The Data to Pivot: Enterprise Visibility and Integration of Your Mission Critical Tooling. Then, contact us to discuss your needs.