Getting Started with Data Modeling – Overview and Importance
Think of how a business plan lays out the written roadmap for companies to understand and make sense of all the moving parts of their business: the drivers, resources, and processes required to achieve success. This plan often serves as the manual companies consult to understand how all the pieces of the business puzzle fit together.
In the same way, large and complex datasets require a structure or a blueprint that allows data analysts to visualize how different data points can be structured and connected to deliver insights for action or decision making.
This underscores the significance of data modeling in the field of data analytics, and it is precisely where data modeling in Microsoft Excel proves invaluable.
In this first chapter of the book, we will break down the concept of data modeling within and beyond Microsoft Excel. The chapter will cover the advantages of using a data model to manage multiple sources of data. You will go on to understand some practical use cases on how to use the data model to look up and reference related tables and understand the architecture and features of Power Pivot, the engine for data modeling in Microsoft Excel. Throughout the journey, best practices will be highlighted and covered.
At the end of the chapter, you will be in a good position to understand how data modeling can help you connect and manage datasets from multiple resources to deliver insights quickly and efficiently in your data analytics project.
The following topics will be covered in this chapter:
- Understanding the concept of data modeling
- The importance of a data model in Microsoft Excel
- Practical use cases for a data model
- Introduction to Power Pivot in Excel
- Best practices with Power Pivot
