Best Data Warehouse Books to Learn Data Warehousing and Business Intelligence
Data Warehouse is a large store of data accumulated from a wide range of sources within a company and used to guide management decisions. It emphasizes the capture of data from diverse sources for access and analysis rather than for transaction processing. It is considered as the core component of business intelligence. Here you will get some of the best Data Warehouse books to start learning Data Warehousing and Business Intelligence.Â
The definitive book on Dimensional Modeling and the Kimball methodology. If you need to learn the basics to advanced method of Dimensional Data Warehouse Modeling and Business Intelligence, this book is a must read and will be kept forever as a reference book/manual. Concise, well-written, and easy to follow.
This book features:
- Data warehousing, Business Intelligence and Dimensional Modeling Primer.
- Kimball Dimensional Modelling Techniques Overview.
- Retail Sales and Inventory Models.
- Procurement Case Study.
- Order Management.
- Accounting Case Study and Bus Matrix.
- Customer Relationship Management.
- Human Resources Management.
- Financial Services.
- Telecommunications Case Study.
- Education and Healthcare.
- Electronic Commerce and Insurance.
- Kimball DW/BI Lifecycle Overview.
- Dimensional Modeling Process and Tasks.
- ETL Subsystems and Techniques.
- ETL System Design.
- Big Data Analytics.
This is a very comprehensive and readable book explaining the ins and outs of the Data Vault methodology and modeling. Very good book and explains everything you need to know starting from scratch about Data Vault and Data Vault 2.0. It covers
everything about data vault, including data modeling, ETL processing,
error handling, metadata, data quality and more, all explained in depth
with sufficient examples that can be immediately put to use.
This book includes:
- Introduction to Data Warehousing.
- Scalable Data Warehouse Architecture.
- The Data Vault 2.0 Methodology.
- Data Vault 2.0 Modelling.
- Intermediate Data Vault Modelling.
- Advanced Data Vault Modelling.
- Dimensional Modelling.
- Physical Data Warehouse Design.
- Master Data Management.
- Metadata Management.
- Data Extraction.
- Loading the Data Vault.
- Implementing Data Quality.
- Loading the Dimensional Information Mart.
- Multidimensional Database.
source for an introduction to databases and all their related parts.
The book includes great explanations and real world examples to get
points across. Well written and gives detailed examples of each concept.
This book contains:
- Development of Database Systems.
- Database Requirements and ER Modelling.
- Relational Database Modelling.
- Update Operations, Anomalies and Normalization.
- SQL Overview.
- Database Implementation and Use.
- Data Warehousing Concepts.
- Data Warehouse Implementation and Use.
- DBMS Functionalities and Database Administration.
Agile Data Warehouse Design is an eminently useful book and a long-needed complement to the dimensional modeling literature. A good
step-by-step guide for capturing data warehousing requirements and
building dimensional models from these requirements through
modelstorming with business
This book delivers:
- How to Model a Data Warehouse.
- Modelling Business Events.
- Modelling Business Dimensions.
- Modelling Business Processes.
- Modelling Star Schemas.
- Design Patterns for People and Organizations, Products and Services.
- Design Patterns for Time and Locations.
- Design Patterns for High Performance Fact Tables and Flexible Measures.
- Design Patterns for Cause and Effect.
It's an amazing book for the newbies into this domain to have an overview of the things happening in data warehouse. This book
gives practical guidelines to follow through the ETL cycle, it does not
matter if you are using an Industry Standard ETL tool or writing your
own ETL process from scratch, this book will be useful for both. Great resource book with understandable explanations and writing.
This book offers:
- Surrounding the requirements.
- ETL Data Structures.
- Cleaning and Conforming.
- Delivering Dimension Tables.
- Delivering Fact Tables.
- Development and Operations.
- Metadata and Responsibilities.
- Real-time ETL Systems.
Good overview and provided a good working knowledge of the queries for Hadoop. This book will guide you to Apache Hive, Hadoop’s data warehouse infrastructure. Concise and easy to understand.
This book covers:
- Overview of Hadoop and MapReduce.
- Installing a Preconfigured Virtual Machine.
- Data Types and File Format.
- HiveOL: Data Definition.
- HiveOL: Data Manipulation.
- HiveOL: Queries.
- HiveOL: Views, Indexes and Designs.
- Schema Design and Tuning.
- Other File Formats and Compression.
- Developing and Functions.
- Customizing Hive File and Record Formats.
- Hive Thrift Service.
- Storage Handlers and NoSQL.
- Security and Locking.
- Hive Integrating and Oozie.
- Hive and Amazon Web Services (AWS).
- HCatalog and Case Studies.
- Glossary and References.
Great Book on Data Warehousing concepts. This is an excellent book for people who are new to data warehousing and just need an overview. It will teach you how to manage a data warehouse project successfully.
This book features:
- The Data Warehouse: Home for your Data Assets.
- Data Warehousing Technology.
- Business Intelligence and Data Warehousing.
- Data Warehousing Projects.
- Business Analysis (OLAP).
- Data Mining.
- Dashboards and Scorecards.
- Building a Winning Data Warehousing Team.
- Capturing Requirements.
- Analyzing Data Resources.
- Delivering the Goods.
- User Testing, Feedback and Acceptance.
- The Information Value Chain.
- Data Warehousing Driving Quality and Integration.
- Working with Data Warehousing Consultants.
- Expanding your Data Warehousing with Unstructured Data.
- 10 Secrets to Managing your Projects successfully.
- 10 Sources of Up-to-date Information about Data Warehousing.
- 10 Mandatory Skills for a Data Warehousing Consultant.
- 10 Subject Areas to Cover with Product Vendors.
book provides some wise advice on the importance of using an ETL
framework, its basic components, how to deal with some common
sources/targets, and how to get started with the all-important metadata
generation needed in order to be effective with BimI.
This book includes:
- Learning BimI.
- Introduction to the BimI Language.
- Basic Staging Operations.
- Importing Metadata.
- Reusing Code, Helper Classes and Methods.
- A Custom BimI Framework.
- Using BimI as an SSIS Design Patterns Engine.
- Integration with a Custom SSIS Execution Framework.
- Metadata Automation.
- Advanced BimI Framework and BimIFlex.
- BimI and Analysis Services.
- BimI for T-SQL and Other Little Helpers.
- Documenting your BimI Solution.
- Troubleshooting Metadata.
- Troubleshooting BimI.
book for those who want to build a data warehouse ASAP. A detailed,
hands-on, step-by-step resource that you can first use to quickly get a
data warehouse up and running, but then keep handy on your bookshelf to
assist in future improvements. This book also contains helpful advice
& tips which is very easy to follow and understand.
This book contains:
- Introduction and Scope.
- Benefits of Data Warehouses and Data Warehouse Automation.
- Proposal Phase.
- Step-by-step Construction of a Rapid Prototype.
- Overview of Data Warehouse Development Goals.
- Installation and Setup of Tools Needed for a Rapid Prototype.
- Create an ETL Group.
- Design Download Tables.
- Flat Table Design.
- Flat Procedure Design.
- Dimension Table Design.
- Dimension Procedure Design.
- Fact Table Design.
- Fact Procedure Design.
- Compiling an ETL Group.
- The 'Queries and Info' Section.
- Junk Dimension Design.
- Bridge Dimension Design.
- Outrigger Dimension Design.
- Pivot Tables.
- Classifying Unknown Tables.
As Data Warehousing technology is the modern trend right now and if you want to get introduced with Data Warehousing and apply it to your business intelligence this book is for you. It will teach you how Data Warehousing reduce complexity in modern era.
This book offers:
- Basic introduction of Data Warehousing.
- How to implement it into the business intelligence.
- What it's core requirements.
- Data Warehouse Architecture.
- Performance Analysis.
- References with real-time examples.
- Easy to follow and understand.