As your database grows, so do your ambitions. When planning to expand, businesses often pour more resources and money into advertising and growth.
Advertising is an obvious choice. More ads mean better brand recognition and trust. But what's driving your campaign? What's your main message?
Look at the success of companies like Slack, Microsoft, Amazon, and Apple. Have you wondered how they keep launching impressive new features? Their secret: big investments in data warehousing projects. But why are these projects so important?
Data is like a window into your business. The more you track, the more insights you get. Well-organized data makes it easier to get the information you need. With this data, you can see how customers interact with your products and services. It highlights the whole flow of your business. Since you can’t watch everything yourself, you rely on your team for key figures. However, relying solely on humans for data can be risky. People might accidentally or purposely distort information by hiding, inflating, or omitting critical data points. When decisions are based on such data, it’s no wonder outcomes might not go as expected.
Smart executives have recognized this problem. They've started consolidating and organizing their in-house data, enabling reporting at any business level without needing human intervention.
Organizing your data is tough, especially if it's scattered across various platforms and databases. This makes data gathering difficult and often needs experts to find the best way to extract data.
Data projects are big because they require multiple people in your organization to come together and be transparent. Even gathering simple business requirements can take weeks or months.
Finding data engineers is easy, but finding good ones is hard. Good data engineers don't look at problems from just a technical standpoint. They need to deeply understand the business and its operations. They should also be capable of gathering business requirements and turning them into technical specs.
Once you have a data pipeline, data lake, and data warehouse, you can create custom dashboards. These dashboards provide clear insights into how your business functions. This includes sign-up flows, conversion rates, user engagement, purchases, drop-offs, and top-performing products and services.
Building a data warehouse is like creating a business oracle. It tells you what has happened in the past, but you need to interpret it. How you read this data and make decisions will guide your future. If you aim to do advanced projects like Machine Learning or develop powerful recommendation systems, building a data warehouse is a crucial step.
