Covers Delta Lake and Data Lakehouse as intrinsic parts of Azure Synapse Analytics

Includes use cases and reference architecture for Synapse Analytics

Presents Synapse SQL best practices

Provides details of Synapse SQL and Synapse Spark architecture and their main components

Chapter Goal: Introducing readers to some of the important core data and analytics concepts as a foundation

No of pages : 15

Sub -Topics

1. Introduction/Background

1. Structured Data

2. Unstructured Data

3. Semi-Structured Data

4. Batch Data

6. Difference between Streaming Data and Batch Data

7. Relational Data and its characteristics

3. Core Analytics Concepts

1. Data Ingestion

2. ETL

2. Data Processing

3. Data Exploration

4. Data Visualization

1. Descriptive

2. Diagnostic

3. Predictive

4. Prescriptive

4. Summary

Chapter Goal: Providing conceptual understanding about traditional / legacy Data Warehouse, Modern Data Warehouse and finally the most modern Data Lakehouse.

No of pages: 25

Sub - Topics

1. Introduction/Background

2. What is Data Warehouse?

3. Why do we need a Data Warehouse?

4. What is Modern Data Warehouse?

6. What is Data Lakehouse?

7. Comparison between Data Warehouse and Data Lakehouse

8. Benefits of Data Lakehouse

9. Examples of Data Lakehouse

10. Summary

Chapter Goal: Building foundational knowledge by introducing Azure Synapse Analytics, its main features and its key services capabilities

No of pages : 20

Sub - Topics:

1. Introduction/Background

2. What is Azure Synapse Analytics?

3. Azure Synapse Analytics vs Azure SQL Datawarehouse

4. Why should you learn Azure Synapse Analytics?

5. Main Features

1. Unified Experience

3. Limitless Scale

4. Instant Clarity

5. Security and Privacy

6. Key Services Capabilities

2. Data Lake Exploration

3. Multiple Language Support

4. Low-Code or Code-Free Data Orchestration

5. Integrated Apache Spark and SQL Engines

7. AI Integration

8. BI Integration

9. Management and Security

7. Summary

Chapter Goal: Explaining Azure Synapse Analytics Core Architecture and its main components as it is very different from traditional Data Warehouse Architecture and its components.

No of pages: 15

Sub - Topics:

1. Introduction/Background

2. High Level Architecture

3. Main Components of Architecture

1. Synapse SQL

2. Synapse Spark

4. Synapse Studio

5. Synapse Link

4. Summary

Chapter Goal: Exploring Synapse SQL in detail including its architecture, its main features with some How-Tos to make the readers familiar with some important activities which can be carried out for Synapse SQL

No of pages: 25

Sub - Topics:

1. Background / Introduction

2. Synapse SQL Architecture Components

1. Azure Storage

2. Control Node

4. Data Movement Service

5. Distributions

3. Synapse SQL Pool

4. Synapse SQL On-Demand

5. Synapse SQL Features

6. Resource Consumption Models

7. Synapse SQL - Best Practices

8. How-Tos

1. Create an Azure Synapse SQL Pool

3. Load Data using COPY Statement

4. Load data from Azure Data Lake Storage for Synapse SQL

5. Load data by using Azure Data Factory

6. Ingest data into Azure Data Lake Storage Gen2

9. Summary

Chapter Goal: Explaining Synapse Sparks and its main components including Delta Lake along with some How-Tos to make the readers familiar with important tasks pertaining to Synapse Spark.

No of pages: 30

Sub - Topics:

1. Introduction/Background

2. What is Apache Spark

3. Synapse Spark Capabilities

4. What is Delta Lake and its importance in Spark?

5. Synapse Spark Job Optimization

6. Development Libraries

7. Apache Spark Machine Learning

8. How-Tos

1. Create Synapse Spark Cluster

2. Load Data using Synapse Spark Cluster

3. Export / Import Data with Apache Spark

9. Summary

Chapter Goal: Introducing Azure Synapse Pipelines and how it integrates with Azure Data Factory. Detailed explanation to various types of Pipeline activities with examples.

No of pages: 20

Sub - Topics:

1. Introduction / Background

2. Overview of Azure Data Factory

4. Data Transformation Activities

5. Control Flow Activities

7. Transformation Pipeline Example

8. Scheduling Pipelines

Chapter Goal: To make readers familiar with Synapse Workspace and Synapse Studio including its main features and its capabilities and to give understanding about how to accomplish some important tasks using workspace and studio.

No of pages: 25

Sub - Topics:

1. What is Synapse Workspace?

2. Workspace Components and Features

3. What is Synapse Studio?

4. Main Features

5. Capabilities (What it can do?)

6. Linking Power BI to Synapse Studio

7. How-To carry out important activities using Studio

8. Summary

Chapter Goal: To explain differences between OLTP and OLAP, why HTAP is required and its benefits and then introducing Synapse Link along with its Cosmos DB integration, its features and use cases.

No of pages: 20

Sub - Topics:

1. Introduction / Background

2. OLTP vs OLAP

3. What is HTAP?

4. HTAP Benefits

5. What is Azure Synapse Link?

6. Azure Cosmos DB Analytical Store

7. Synapse Link Features

8. Synapse Link Use Cases

Chapter Goal: To make readers familiar with Synapse Workspace and Synapse Studio including its main features and its capabilities and to give understanding about how to accomplish some important tasks using workspace and studio.

No of pages: 15

Sub - Topics:

1. Introduction / Background

2. Where you should use Synapse Analytics?

3. Where it should not be used?

4. Few Examples of Use cases of Synapse Analytics

5. Reference Architecture for Synapse Analytics

6. Summary