Chapter 1: Core Data and Analytics Concepts 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
2. Core Data Concepts 1. Structured Data
2. Unstructured Data
3. Semi-Structured Data
4. Batch Data
5. Streaming Data 6. Difference between Streaming Data and Batch Data
7. Relational Data and its characteristics
3. Core Analytics Concepts
1. Data Ingestion
1. ELT 2. ETL
2. Data Processing
3. Data Exploration
4. Data Visualization
5. Analytics Techniques 1. Descriptive
2. Diagnostic
3. Predictive
4. Prescriptive
5. Cognitive 4. Summary
Chapter 2: Modern Data Warehouse and Data Lakehouse 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?
5. Comparison between Traditional Data Warehouse and 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 3: Introduction to Azure Synapse Analytics 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
2. Powerful Insights 3. Limitless Scale
4. Instant Clarity
5. Security and Privacy
6. Key Services Capabilities
1. EDW 2. Data Lake Exploration
3. Multiple Language Support
About the Author: Bhadresh Shiyal is an Azure data architect and Azure data engineer. For the past seven years, he has been working with a large multi-national IT corporation as Solutions Architect. Prior to that, he spent almost a decade in private and public sector banks in India in various IT positions working on various Microsoft technologies. He has 18 years of IT experience, including working for two years on an international assignment from London. He has much experience in application design, development, and deployment. He has worked on various technologies, including Visual Basic, SQL Server, SharePoint Technologies, .NET MVC, O365, Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage Gen1/Gen2, Azure SQL Data Warehouse, Power BI, Spark SQL, Scala, Delta Lake, Azure Machine Learning, Azure Information Protection, Azure .NET SDK, Azure DevOps, and more.
He holds multiple Azure certifications that include Microsoft Certified Azure Solutions Architect Expert, Microsoft Certified Azure Data Engineer Associate, Microsoft Certified Azure Data Scientist Associate, and Microsoft Certified Azure Data Analyst Associate.
Bhadresh has worked as Solutions Architect on a large-scale Azure Data Lake implementation project as well as on a data transformation project and on large-scale customized content management systems. He has also worked as Technical Reviewer for the book Data Science using Azure, prior to authoring this book.
