Mastering Azure Analytics, 1st Edition

Preface

If you are building software solutions today, odds are that you have a data problem. You might even have an advanced analytics problem or one that requires machine learning. The trouble is that the world of software development and those of big data and advanced analytics seem like they are light years apart—they use different software stacks, different terminology, and often different engineering approaches, and there are lots of choices. The aim of this book is to provide you with a map of the galaxy that helps you chart your course to wrangling insights and guidance out of your data—irrespective of whether that data is arriving at warp speed from IoT sensors or at the glacial pace of decades of historical data.

The structure of this book is designed along the path of a data pipeline that aims to ingest, process, store, and deliver data along both real-time (hot data) and batch (cold data) paths. The waypoints in the map to your data pipeline are groups of Azure services, and each is covered in one or more chapters. We describe each service and tool that you should consider for a particular step in your pipeline. Another way to think about it is to look at each phase of the analytics pipeline as a toolbox onto itself: which Azure service would you use for long-term storage? We show you how to use Azure Storage and Azure Data Lake Store. What about storage of streaming data? We give you the options—including Azure Stream Analytics, Azure HDInsight with Storm or Spark, ...