Welcome back to Z to A Pulse, the monthly Zuci Systems newsletter covering the most insightful yet unspoken topics around engineering excellence.

In this issue, we will explore the concept of a distributed BI network and how it offers a lean alternative to traditional enterprise BI projects.

Today’s edition is brought to you by me, Janaha Vivek. If you enjoy reading Z to A Pulse, consider sharing it with a friend.

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Are you tired of the long, complex, and costly process of implementing enterprise BI projects? Are you looking for a more efficient and lean approach to business intelligence? Distributed BI Network (DBIN) is what you need.

With a Distributed BI Network, organizations can leverage the power of multiple BI tools and technologies without the need for a centralized BI infrastructure. This approach offers numerous benefits, including faster time-to-insight, improved data accessibility, and greater flexibility in data analysis.

In this edition of our newsletter, Kalyan Allam, our senior technical manager – Business Intelligence, with over a decade of experience in data and analytics, will uncover the topic of Distributed BI networks.

Kalyan will delve into the key benefits and challenges of this lean alternative to traditional enterprise BI projects and provide insights on how organizations can take advantage of this exciting new approach to business intelligence. Stay tuned for more insights on this cutting-edge topic!

Technology Expert of the Month

Kalyan Allam, Senior Technical Manager – Business Intelligence, Zuci Systems.

Let’s drop right in, shall we?

Janaha: Why do enterprise BI projects lose momentum and fail?

Kalyan: There are many reasons why enterprise BI projects can lose momentum and fail. One common reason is a lack of clear goals and objectives. Without a clear understanding of what the project is trying to achieve, it can be difficult to keep the project on track and ensure that resources are being used effectively.

Imagine a company where each department comes together to create a single enterprise-level BI dashboard. On the surface, this seems like a great idea. After all, having all the data in one place makes it easier to see the big picture and make informed decisions. However, as the project progresses, it becomes clear that the dashboard does not tell the full story for each department.

For example, the data that is important for the operations team may not be as relevant for the sales team. As a result, the sales team may not see the value in the dashboard and lose interest in the project. This lack of buy-in can lead to a lack of resources and support, which can ultimately cause the project to lose momentum and fail.

Furthermore, how the data is interpreted can also lead to different conclusions being drawn by different people. For example, the same data may be seen as a positive trend by one person but as a negative trend by another. This can create confusion and conflict within the organization, making it difficult to move the project forward.

Overall, enterprise BI projects need clear goals and objectives, buy-in from key stakeholders, and a focus on the needs of each department. Without these elements, the project may struggle to gain traction and ultimately fail.

Janaha: Is there an alternative option for an enterprise that wants to lean on BI projects?

Kalyan: As a seasoned project consultant in data analytics and business intelligence, I strongly believe in the value of a distributed approach to BI for enterprises.

By embedding BI capabilities in every department and at every level of the organization, companies can enable decentralized decision-making and empower individuals and teams to access and analyze data on their own terms.

Distributed BI Network (DBIN) allows for the seamless flow of data and analysis throughout the organization. This can lead to greater agility and responsiveness to changing business needs and a culture of data-driven decision-making throughout the organization.

Of course, implementing a distributed BI network requires careful planning and execution, as it may involve changes to organizational structure, data management processes, and technology infrastructure. It is also important to ensure that a top-down push is crucial for the success of a distributed business intelligence initiative.

Just as a river flows through multiple channels and branches off into smaller streams, the BI initiative can also branch off into different departments and teams, each creating their own channel to access and use the data in a way that makes sense for their specific needs and goals.

But without the support and guidance of top management, the BI initiative may struggle to gain traction and make a meaningful impact on the organization. It is important for top management to set the vision and strategy for the BI initiative and to provide the necessary resources and support for its implementation and ongoing success.

Janaha: For a successful Distributed BI project, is a single source of truth system important?

Kalyan: I do believe that a single source of truth system can be beneficial for a distributed BI project. A centralized system for storing and managing data can help ensure that everyone in the organization is working with accurate and consistent data, which can be critical for making informed decisions and driving better outcomes.

However, it is important to recognize that building a single source of truth can be a challenging and time-consuming process, and it is not always necessary or even feasible for all organizations. In some cases, the effort and resources required to build a single source of truth may outweigh the potential benefits.

It is also important to remember that the ultimate goal of BI is to gain insights and drive better outcomes for the business, not just to have a single database which captures all the functional data. While a single source of truth can be helpful, it is not the only factor in the success of a distributed BI project.

There are many tools and technologies available today that can help organizations access and analyze data from multiple sources, even if they do not have a single source of truth in place.

By focusing on the insights and outcomes that can be achieved through BI rather than on the specific approach to data management, organizations can still achieve success with their distributed BI projects.

That is my point. A single source of truth is needed, but that should not be a stopping point for you to achieve your BI goals.

Janaha: Can you share a case study on how you approached a Distributed BI Network (DBIN)?

Kalyan: In my experience, I have worked on many projects, and one project stands out as an example of how a distributed BI network can evolve and be successful, even if the initial enterprise-level BI project failed.

I was part of a project with a large company that developed a BI roadmap for the entire organization. The goal was to create a network of dashboards and self-service analytics tools accessible to all departments and teams. We built close to 100 dashboards and worked with the company to promote these tools to the various teams and departments.

However, despite our efforts, the adoption of the dashboards and tools was low. Many teams and departments preferred to stick with their existing methods and tools, and the executive-level support for the BI initiative waned. As a result, the enterprise-level BI project was eventually archived and deemed a failure.

However, something interesting happened during this process. Many of the teams and departments saw the value of BI and started developing their own BI projects in addition to the ones we were already working on. These projects were tailored to each team or department’s specific needs and goals, and they successfully drove insights and better outcomes.

As a result, a distributed BI network organically emerged within the company, with each team or department having its own set of dashboards and tools. While there was no longer a single source of truth or a central BI project that everyone in the organization was using, the overall BI capabilities of the company were stronger and more effective as a result of the distributed approach.

Also, though each department has its own BI tools and consultants, they all come under a single department – BI, a network parallel to the company’s operational/organizational structure. This gave us an amazing opportunity for all the BI consultants to come together and bring synergy which wasn’t possible in the Enterprise BI method.

Today, we are working with the company to support and enhance their distributed BI network, helping to ensure that all teams and departments have the tools and support they need to drive insights and better outcomes for the business. This experience has been a success story for the distributed BI network and a failure story for the enterprise-level BI project. Still, overall, it has been a successful experience for the company’s BI efforts.

Janaha: In your opinion, what is the future of business intelligence?

Kalyan: The future of business intelligence will not be centered around a one-stop-shop platform that tries to solve every problem with a single solution. Instead, organizations will continue to have a diverse range of tools and technologies that they use to solve specific problems and drive insights.

There are already many companies and products that specialize in different aspects of BI, such as data integration and ETL, visualization, and prescriptive analytics. These tools and technologies are all valuable and can be combined to create a robust BI ecosystem.

For example, Tableau is known for its strong visualization capabilities, while Power BI excels in ETL and distribution. Domo is a strong tool for quick integration with various data sets. While some companies are trying to bring these capabilities together in one platform, I do not believe this will be BI’s future.

Instead, I believe that the future of BI will involve organizations choosing the right tools and technologies for specific problems and goals rather than trying to find a single solution that can solve everything. This means that organizations will need to be flexible and open to using a variety of tools and technologies rather than trying to force everything into a single platform. By adopting this mindset and approach, organizations can stay at the forefront of BI and continue to drive insights and better outcomes for their business.

Check out this video from Kalyan where he explains the three different types of analytics in simple terms and why prescriptive analytics is the future of data analytics.

In conclusion, a successful BI project requires a strong foundation of support from top management and buy-in from middle and senior managers who will be using the reports and tools. A distributed BI network can be a powerful approach, allowing teams and departments to access and use data in a way that makes sense for their specific needs and goals. While a single source of truth can be beneficial, it is not necessary for a successful BI project. And organizations should be open to using various tools and technologies to drive insights and better outcomes for their business.

Originally featured in our LinkedIn Newsletter, ZtoA Pulse.

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