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Best Books to Learn Data Modeling Beginners to Advanced

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Best Books to Learn Data Modeling
Best Books to Learn Data Modeling

Are you looking for the best books on Data Modeling?… If yes, then this article is for you. In this article, you will find the Best Books to Learn Data Modeling for Beginners & advanced like Beginner courses, and Practice test coursesSo, check these Best Books to Learn Data Modeling for Beginners and find the Best Books to Learn Data Modeling for Beginners to Advanced according to your need.

In the previous article, I shared the Best Data Science Books for Beginners to Advanced to read in 2022, you can go through the list and enjoy reading.

Best Books to Learn Data Modeling for Beginners to Advanced to know in 2022

Data Modeling: A Beginner’s Guide

Learn how to create data models that allow complex data to be analyzed, manipulated, extracted, and reported upon accurately. Data Modeling: A Beginner’s Guide teaches you techniques for gathering business requirements and using them to produce conceptual, logical, and physical database designs.

You’ll get details on Unified Modeling Language (UML), normalization, incorporating business rules, handling temporal data, and analytical database design. The methods presented in this fast-paced tutorial are applicable to any database management system, regardless of vendor.

  • Key Skills & Concepts–Chapter-opening lists of specific skills covered in the chapter
  • Ask the expert–Q&A sections filled with bonus information and helpful tips
  • Try This–Hands-on exercises that show you how to apply your skills
  • Notes–Extra information related to the topic being covered
  • Self Tests–Chapter-ending quizzes to test your knowledge

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Microsoft Excel Data Analysis and Business Modeling

Master business modeling and analysis techniques with Microsoft Excel and transform data into bottom-line results. Award-winning educator Wayne Winston’s hands-on, scenario-focused guide helps you use today’s Excel to ask the right questions and get accurate, actionable answers.

More extensively updated than any previous edition, new coverage ranges from one-click data analysis to STOCKHISTORY, dynamic arrays to Power Query, and includes six new chapters. Practice with over 900 problems, many based on real challenges faced by working analysts.

  • Quickly transition from Excel basics to sophisticated analytics
  • Use recent Power Query enhancements to connect, combine, and transform data sources more effectively
  • Use the LAMBDA and LAMBDA helper functions to create Custom Functions without VBA
  • Use New Data Types to import data including stock prices, weather, information on geographic areas, universities, movies, and music
  • Build more sophisticated and compelling charts
  • Use the new XLOOKUP function to revolutionize your lookup formulas
  • Master new Dynamic Array formulas that allow you to sort and filter data with formulas and find all UNIQUE entries
  • Illuminate insights from geographic and temporal data with 3D Maps
  • Improve decision-making with probability, Bayes’ theorem, and Monte Carlo simulation and scenarios
  • Use Excel trend curves, multiple regression, and exponential smoothing for predictive analytics
  • Use Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook

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An Introduction to Agile Data Engineering Using Data Vault 2.0: Better Data Modeling

The world of data warehousing is changing. Big Data & Agile are hot topics. But companies still need to collect, report, and analyze their data. Usually this requires some form of data warehousing or business intelligence system.

So how do we do that in the modern IT landscape in a way that allows us to be agile and either deal directly or indirectly with unstructured and semi structured data? The Data Vault System of Business Intelligence provides a method and approach to modeling your enterprise data warehouse (EDW) that is agile, flexible, and scalable.

This book will give you a short introduction to Agile Data Engineering for Data Warehousing and Data Vault 2.0. I will explain why you should be trying to become Agile, some of the history and rationale for Data Vault 2.0, and then show you the basics for how to build a data warehouse model using the Data Vault 2.0 standards.

In addition, I will cover some details about the Business Data Vault (what it is) and then how to build a virtual Information Mart off your Data Vault and Business Vault using the Data Vault 2.0 architecture. So if you want to start learning about Agile Data Engineering with Data Vault 2.0, this book is for you.

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The Data Model Resource Book Universal Patterns for Data Modeling

the best-selling “Data Model Resource Book” series revolutionizes the data modeling discipline by answering the question “How can you save significant time while improving the quality of any type of data modeling effort?” In contrast to the first two volumes, this new volume focuses on the fundamental, underlying patterns that affect over 50 percent of most data modeling efforts.

These patterns can be used to considerably reduce modeling time and cost, to jump-start data modeling efforts, as standards and guidelines to increase data model consistency and quality, and as an objective source against which an enterprise can evaluate data models.

For each pattern, numerous alternatives are provided, ranging from very specific to very generalized ways of modeling. Len Silverston and Paul Agnew point out the pros and cons of these alternatives and provide guidelines to help you make appropriate decisions depending on the set of circumstances faced. In developing and documenting these patterns, the authors share an invaluable set of foundational tools for anyone involved in data modeling, from the novice to the expert.

  • Model the most prevalent data modeling constructs such as ways to model roles, hierarchies, classifications, statuses, contact information, and business rules
  • Re-use a powerful library of core patterns for data modeling
  • Model at different levels of generalization
  • Evaluate the pros and cons of specific versus generalized models
  • Apply the patterns in many types of data modeling efforts, such as prototypes, applications, enterprise data models, data warehouses, and master data management efforts
  • Gain buy-in regarding the use of patterns and/or standardizing on these patterns

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The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling

This new third edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever. It covers new and enhanced star schema dimensional modeling patterns, adds two new chapters on ETL techniques, includes new and expanded business matrices for 12 case studies, and more.

  • Authored by Ralph Kimball and Margy Ross, known worldwide as educators, consultants, and influential thought leaders in data warehousing and business intelligence
  • Begins with fundamental design recommendations and progresses through increasingly complex scenarios
  • Presents unique modeling techniques for business applications such as inventory management, procurement, invoicing, accounting, customer relationship management, big data analytics, and more
  • Draws real-world case studies from a variety of industries, including retail sales, financial services, telecommunications, education, health care, insurance, e-commerce, and more

Design dimensional databases that are easy to understand and provide fast query responses with The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition.

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Expert Data Modeling with Power BI: Get the best out of Power BI by building optimized data models for reporting and business needs

This book is a comprehensive guide to understanding the ins and outs of data modeling and how to create data models using Power BI confidently.

You’ll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization.

In this book, you’ll explore how to use data modeling and navigation techniques to define relationships and create a data model before defining new metrics and performing custom calculations using modeling features. As you advance through the chapters, the book will demonstrate how to create full-fledged data models, enabling you to create efficient data models and simpler DAX code with new data modeling features.

With the help of examples, you’ll discover how you can solve business challenges by building optimal data models and changing your existing data models to meet evolving business requirements.

Finally, you’ll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks.

By the end of this Power BI book, you’ll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support reporting and data analytics.

  • Implement virtual tables and time intelligence functionalities in DAX to build a powerful model
  • Identify Dimension and Fact tables and implement them in Power Query Editor
  • Deal with advanced data preparation scenarios while building Star Schema
  • Explore best practices for data preparation and modeling
  • Discover different hierarchies and their common pitfalls
  • Understand complex data models and how to decrease the level of model complexity with different approaches
  • Learn advanced data modeling techniques such as aggregations, incremental refresh, and RLS/OLS

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Statistical Modeling and Applications in Data Analysis

This book has been written with the upper level undergraduate student in mind and provides a smooth transition into the study of the modeling and analysis of common statistical data procedures and methods. The examples have been worked from a tutorial perspective and a step by step process is provided beginning with the specified problem and ending with the final analytical conclusion. This method will benefit individuals who plan to pursue post undergraduate level studies in the fields of both academia or the corporate workforce, making this an excellent desk reference.

View this Book on Amazon

And here the list ends. So, these are the Best Books to Learn Data Modeling for Beginners to Advanced. I will keep adding more Best Books on Data Modeling to this list.

Conclusion

I hope these Best Books to Learn Data Modeling for Beginners to Advanced will definitely help you to enhance your skills. If you have any doubts or questions, feel free to ask me in the comment section.

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