1 Introducing the data platform

This chapter covers

  • Driving change in the world of analytics data
  • Understanding the growth of data volume, variety, and velocity, and why the traditional data warehouse can’t keep up
  • Learning why data lakes alone aren’t the answer
  • Discussing the emergence of the cloud data platform
  • Studying the core building blocks of the cloud data platform
  • Viewing sample use cases for cloud data platforms

Every business, whether it realizes it or not, requires analytics. It’s a fact. There has always been a need to measure important business metrics and make decisions based on these measurements. Questions such as “How many items did we sell last month?” and “What’s the fastest way to ship a package from A to B?” have evolved to “How many new website customers purchased a premium subscription?” and “What does my IoT data tell me about customer behavior?”

1.1 The trends behind the change from data warehouses to data platforms

1.2 Data warehouses struggle with data variety, volume, and velocity

1.2.1 Variety

1.2.2 Volume

1.2.3 Velocity

1.2.4 All the V’s at once

1.3 Data lakes to the rescue?

1.4 Along came the cloud

1.5 Cloud, data lakes, and data warehouses: The emergence of cloud data platforms

1.6 Building blocks of a cloud data platform

1.6.1 Ingestion layer

1.6.2 Storage layer

1.6.3 Processing layer

1.6.4 Serving layer

1.7 How the cloud data platform deals with the three V’s