Book Image

Azure Data Engineer Associate Certification Guide

By : Newton Alex
Book Image

Azure Data Engineer Associate Certification Guide

By: Newton Alex

Overview of this book

Azure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout the chapters, you'll learn about the various Azure components involved in building the data systems and will explore them using a wide range of real-world use cases. Finally, you’ll work on sample questions and answers to familiarize yourself with the pattern of the exam. By the end of this Azure book, you'll have gained the confidence you need to pass the DP-203 exam with ease and land your dream job in data engineering.
Table of Contents (23 chapters)
1
Part 1: Azure Basics
3
Part 2: Data Storage
10
Part 3: Design and Develop Data Processing (25-30%)
15
Part 4: Design and Implement Data Security (10-15%)
17
Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
20
Part 6: Practice Exercises

Monitoring and updating statistics about data across a system

Statistics is an important concept in query optimization. Generating statistics is the process of collecting metadata about your data—such as the number of rows, the size of tables, and so on—which can be used as additional inputs by the SQL engine to optimize query plans. For example, if two tables have to be joined and one table is very small, the SQL engine can use this statistical information to pick a query plan that works best for such highly skewed tables. The Synapse SQL pool engine uses something known as cost-based optimizers (CBOs). These optimizers choose the least expensive query plan from a set of query plans that can be generated for a given SQL script.

Let's look at how to create statistics for both Synapse dedicated and serverless pools.

Creating statistics for Synapse dedicated pools

You can enable statistics in Synapse SQL dedicated pools using the following command:

ALTER...