Any organization aiming to leverage the power of data-driven decision-making stands to benefit greatly from a successful Data Warehouse project. A well-designed Data Warehouse not only centralizes your data but also guarantees that it is reliable, scalable, maintainable, and usable by stakeholders.
Over the past few months, my team and I have launched a new Data Warehouse project in production. The opportunity to start from scratch is always a valuable chance to gain new insights and expertise. I would like to share the experiences from this success story in the hope that they will be as beneficial to others as they have been to us.
Understand Business Requirements
The first step in starting any project, not only a Data Warehouse, is to fully understand the business requirements. This is the difference between success and failure, not just a formality. If you skip this step, I can tell you with certainty that your project will be a waste of time, energy, and resources.
To really understand what business wants to see and what your team needs to do, it’s essential to spend time talking to the people who will be using the Data Warehouse. What do they hope to accomplish? How will it help them do their jobs better? How do they plan to use the data? Getting a clear picture of their goals is essential to making sure your project is on the right track.
However, this is where things often get complicated. People usually do not understand each other, especially people in different departments who have different perspectives, priorities, and terminologies. Sometimes people do not even understand what they are saying. Business guys are the ones who are easily attracted to marketing buzzwords on the Internet believing that these terms are the solutions to their problems. I have to say that the marketing departments of data companies do a really good job of re-inventing new names for the similar term. During this project, there were dozens of times the guys told me let’s use this tool, why not use this technology, money is not a problem (until they actually got the bill).
In one of my previous projects, a stakeholder told me that he wanted a visually stunning real-time dashboard that would make the numbers dance instantly whenever users did something in the web application. And I had to explain to him:
- Visually stunning: Yes, the data analysts team can always help you with that.
- Real-time: There is no real time. If the sun disappears, we can know it only after 8 minutes. So does the data.
- We do not really need it. Business is not going to sit still and watch the numbers dance every second.
Patience is the key. They do not understand those technical buzzwords. Yes. But isn’t that why you are here as a technical specialist? Your responsibility is to listen to them, understand them, empathize with them, and tell them what you will do to help them. Your job is to translate their requirements into a workable solution.
Remember that the business stakeholders are not only the end users, but also the investors. Without their buy-in, the project can’t even get off the ground. They are funding the project, and they deserve the best service.
By starting with a clear understanding of business requirements, you set the stage for a Data Warehouse project that is aligned with the organization’s goals, ensuring that the final product delivers real value.
Understand System
A Data Warehouse is not an isolated island. It is more like a bustling city that relies on a network of interconnected systems. It receives supplies from surrounding farms and industrial areas. Since Data Warehouse pulls data from other systems, you can not build a successful Data Warehouse without understanding how the other systems work.
Imagine stakeholders telling you they want the sales figure. Then you need to know exactly which systems hold the sales number. How is that number populated in each system? It may be manually entered by users, it may be automatically calculated, it may be synchronized from other sources, it may be read-only or editable… You need to know all the surrounding information to decide the source of truth for the number we desire. You may argue that all you need to do is copy the source database over and the business will know what to do with the data. Believe me, they don’t. In fact, they have never seen the database a day in their lives. And you are the one who will tell them what they can do with your Data Warehouse.
And not knowing how the system works also risks your project design. You certainly don’t want to discover a surprise when you’re almost done with the implementation, such as a scheduled job that archives data from the database daily. If you had known that from the beginning, your design would have been very different.
Understanding the entire system in detail can be time-consuming. You should have a good sense of how the interconnected systems work together, but don’t expect to understand them in detail at the beginning of your project. Instead, I would suggest building strong relationships with the teams responsible for maintaining these systems. Meet with them, tell them what you are doing, and ask for their advice and insights. They are a goldmine of information. You can also experiment with sandbox environments and databases to uncover hidden patterns and processes.
Design a reliable Data Warehouse
Reliability is the backbone of any Data Warehouse. If your business can’t rely on the data coming out of your Data Warehouse, your project is completely a failure.
Having a solid testing strategy will greatly help. Testing is not just about finding bugs, it’s about building confidence. When you start designing the data warehouse, think less about the time when the system is running happily, there is nothing for us to do if the system keeps running as it should. Think more about the time when the system is not working and what we are going to do in that time.
And even if you do your best, bugs and issues will still happen. Don’t expect your system to be bug-free; instead, build processes to handle issues as soon as they arise. And most importantly, be transparent. If the business comes to you and asks about an issue they found, tell them what happened and what you are doing to help. Transparency is the key to trust. If you tell a lie, you are part of the problem; if you are transparent, you are part of the solution. A reliable Data Warehouse isn’t just about technology. It’s about building trust.
Choose the right tool for the right job
To build a Data Warehouse, you need a toolbox filled with different pieces to complete the picture: tools for copying data, transforming it, orchestrating jobs, and more. It is technically possible to create the tools yourself, especially if you are in a big corporation and want to control every aspect of the technology. However, in most of the cases, it is impractical. You do not have enough resources to own the technology. Thus, developing a Data Warehouse solution usually means picking the available tools and services and making them work together.
The real challenge is choosing the right tools. Beware of your enemies, the shiny marketing promises. The person who writes those buzzwords may not be the one who writes the code. Sometimes I don’t understand what they wrote, and I think they don’t understand what they wrote either. These tools are very expensive. It is important to avoid overkill. Focus on what your business really needs, not just what sounds cool. We are not going to use the most popular or the most expensive tools; we are going to find the right fit for our specific needs.
Start small, Grow big
Your investors do not have infinite patience. They want to see progress and value. Building something small but functional is far better than promising a grand project that never finish. By starting small, you can quickly deliver value and gather feedback from users.
With limited resources, we can not get everything done at once. It is important to prioritize. What matters most to your business? What will deliver the biggest impact to your customers? Concentrate on delivering those core features first. You can break the project into phases, which is a good practice. Each phase focuses on specific business requirements, data sources, or user groups. And you can gradually expand the capabilities of the Data Warehouse.
Engage users
A Data Warehouse is not just a technical marvel. It is a tool for your business. To ensure it delivers maximum value, you need to involve your users from the very beginning.
Imagine building a house without consulting the people who will live in it. People can still live in it, but they never feel it is their home. By involving them early and often, you will gain valuable insight into their needs, expectations, and challenges.
How can you engage your users?
- Involve them in the planning phase: Understand their data needs, pain points, and desired outcomes.
- Provide regular updates: Keep them informed about project progress and involve them in decision-making.
- Offer training and support: Equip users with the skills to effectively use the Data Warehouse.
- Gather feedback: Encourage users to share their thoughts and suggestions for improvement.
Remember that if you can not engage your users, any slightly higher number in their reports will quickly become your problem. If you can engage them and make them feel like they are part of the project, then any issue will become everyone’s problem.
Conclusion
Building a successful Data Warehouse is a challenging journey that requires careful planning, execution, and continuous improvement. It all starts with a deep understanding of the business requirements to ensure that every decision is aligned with the organization’s goals. Start small, iterate often, and always keep the user at the center of your efforts. A successful Data Warehouse is a collaboration between the engineering team and the business. By working together, you can create a solution that truly delivers value.