Blockchain Data Analytics For Dummies

Chapter 14

Calling on Existing Frameworks

IN THIS CHAPTER

Leveraging quality and compliance

Using a framework to keep the focus on results

Reducing testing effects by using pretested components

Increasing efficiency through frameworks

Streamlining your analytics life cycle

In Chapter 13, you learn about writing analytics models from scratch. Although I focus only on the Python language in this book, I cover several other languages you can use to develop effective data analytics models that interact with blockchain data.

Building models from scratch isn’t your only option. You can build models also by using one of the growing number of analytics frameworks. Instead of just using libraries to carry out model-specific calculations, a framework can abstract away many of the decisions you have to make when building models manually. A framework is essentially a collection of libraries and services that provide prebuilt analytics functionality. You provide the data and some configuration ...