Chapter 1: Balancing the Benefits of Data Lakes Over Data Warehouses

Is the Data Warehouse dead with the advent of Data Lakes? There is disagreement everywhere about the need for Data Warehousing in a modern data estate. With the rise of Data Lakes and Big Data technology, many people use other, newer technologies compared to databases for their analytical efforts. Establishing a data-driven company seems to be possible without all those narrow definitions and planned structures, the ETL/ELT, and all the indexing for performance. But when we examine the technology carefully, when we compare the requirements that are formulated in analytical projects, free of prejudice to the functionality that the chosen services or software packages can deliver, we often find gaps on both ends. This chapter discusses the capabilities of Data Warehousing and Data Lakes and introduces the concept of the Modern Data Warehouse.

With all the innovations that have been brought to us in the last few years, such as faster hardware, new technologies, and new dogmas such as the Data Lake, older concepts and methods are being questioned and challenged. In this chapter, I would like to explore the evolution of the analytical world and try to answer the question, is the Data Warehouse really obsolete?

We'll find out by covering the following topics:

• Distinguishing between Data Warehouses and Data Lakes
• Understanding the opportunities of modern cloud computing
• Exploring the benefits of AI and ML
• Answering the question