Data Modeling With Tableau
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Data Modeling With Tableau
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Author : Kirk Munroe
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-12-30
Data Modeling With Tableau written by Kirk Munroe and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-30 with Computers categories.
Save time analyzing volumes of data using best practices to extract, model, and create insights from your data Key FeaturesMaster best practices in data modeling with Tableau Prep Builder and Tableau DesktopApply Tableau Server and Cloud to create and extend data modelsBuild organizational data models based on data and content governance best practicesBook Description Tableau is unlike most other BI platforms that have a single data modeling tool and enterprise data model (for example, LookML from Google's Looker). That doesn't mean Tableau doesn't have enterprise data governance; it is both robust and very flexible. This book will help you build a data-driven organization with the proper use of Tableau governance models. Data Modeling with Tableau is an extensive guide, complete with step-by-step explanations of essential concepts, practical examples, and hands-on exercises. As you progress through the chapters, you will learn the role that Tableau Prep Builder and Tableau Desktop each play in data modeling. You'll also explore the components of Tableau Server and Cloud that make data modeling more robust, secure, and performant. Moreover, by extending data models for Ask and Explain Data, you'll gain the knowledge required to extend analytics to more people in their organizations, leading to better data-driven decisions. Finally, this book will get into the entire Tableau stack and get the techniques required to build the right level of governance into Tableau data models for the right use cases. By the end of this Tableau book, you'll have a firm understanding of how to leverage data modeling in Tableau to benefit your organization. What you will learnShowcase Tableau published data sources and embedded connectionsApply Ask Data in data cataloging and natural language queryExhibit features of Tableau Prep Builder with hands-on exercisesModel data with Tableau Desktop through examplesFormulate a governed data strategy using Tableau Server and CloudOptimize data models for Ask and Explain DataWho this book is for This book is for data analysts and business analysts who are looking to expand their data skills, offering a broad foundation to build better data models in Tableau for easier analysis and better query performance. It will also benefit individuals responsible for making trusted and secure data available to their organization through Tableau, such as data stewards and others who work to take enterprise data and make it more accessible to business analysts.
Data Modeling With Snowflake
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Author : Serge Gershkovich
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-05-31
Data Modeling With Snowflake written by Serge Gershkovich and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Computers categories.
Discover how Snowflake's unique objects and features can be used to leverage universal modeling techniques through real-world examples and SQL recipes Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn core modeling techniques tied to practical examples using native Snowflake architecture Adopt a universal modeling language to communicate business value to functional teams Go beyond physical modeling with SQL recipes to transform and shape your Snowflake data Book DescriptionThe Snowflake Data Cloud is one of the fastest-growing platforms for data warehousing and application workloads. Snowflake's scalable, cloud-native architecture and expansive set of features and objects enables you to deliver data solutions quicker than ever before. Yet, we must ensure that these solutions are developed using recommended design patterns and accompanied by documentation that’s easily accessible to everyone in the organization. This book will help you get familiar with simple and practical data modeling frameworks that accelerate agile design and evolve with the project from concept to code. These universal principles have helped guide database design for decades, and this book pairs them with unique Snowflake-native objects and examples like never before – giving you a two-for-one crash course in theory as well as direct application. By the end of this Snowflake book, you’ll have learned how to leverage Snowflake’s innovative features, such as time travel, zero-copy cloning, and change-data-capture, to create cost-effective, efficient designs through time-tested modeling principles that are easily digestible when coupled with real-world examples.What you will learn Discover the time-saving benefits and applications of data modeling Learn about Snowflake's cloud-native architecture and its features Understand and apply modeling techniques using Snowflake objects Universal modeling concepts and language through Snowflake objects Get comfortable reading and transforming semistructured data Learn directly with pre-built recipes and examples Learn to apply modeling frameworks from Star to Data Vault Who this book is for This book is for developers working with SQL who are looking to build a strong foundation in modeling best practices and gain an understanding of where they can be effectively applied to save time and effort. Whether you’re an ace in SQL logic or starting out in database design, this book will equip you with the practical foundations of data modeling to guide you on your data journey with Snowflake. Developers who’ve recently discovered Snowflake will be able to uncover its core features and learn to incorporate them into universal modeling frameworks.
Data Modeling With Microsoft Excel
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Author : Bernard Obeng Boateng
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-11-30
Data Modeling With Microsoft Excel written by Bernard Obeng Boateng and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-30 with Computers categories.
Save time analyzing volumes of data using a structured method to extract, model, and create insights from your data Key Features Acquire expertise in using Excel’s Data Model and Power Pivot to connect and analyze multiple sources of data Create key performance indicators for decision making using DAX and Cube functions Apply your knowledge of Data Model to build an interactive dashboard that delivers key insights to your users Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMicrosoft Excel's BI solutions have evolved, offering users more flexibility and control over analyzing data directly in Excel. Features like PivotTables, Data Model, Power Query, and Power Pivot empower Excel users to efficiently get, transform, model, aggregate, and visualize data. Data Modeling with Microsoft Excel offers a practical way to demystify the use and application of these tools using real-world examples and simple illustrations. This book will introduce you to the world of data modeling in Excel, as well as definitions and best practices in data structuring for both normalized and denormalized data. The next set of chapters will take you through the useful features of Data Model and Power Pivot, helping you get to grips with the types of schemas (snowflake and star) and create relationships within multiple tables. You’ll also understand how to create powerful and flexible measures using DAX and Cube functions. By the end of this book, you’ll be able to apply the acquired knowledge in real-world scenarios and build an interactive dashboard that will help you make important decisions.What you will learn Implement the concept of data modeling within and beyond Excel Get, transform, model, aggregate, and visualize data with Power Query Understand best practices for data structuring in MS Excel Build powerful measures using DAX from the Data Model Generate flexible calculations using Cube functions Design engaging dashboards for your users Who this book is for This book is for Excel users looking for hands-on and effective methods to manage and analyze large volumes of data within Microsoft Excel using Power Pivot. Whether you’re new or already familiar with Excel’s data analytics tools, this book will give you further insights on how you can apply Power Pivot, Data Model, DAX measures, and Cube functions to save time on routine data management tasks. An understanding of Excel’s features like tables, PivotTable, and some basic aggregating functions will be helpful but not necessary to make the most of this book.
Data Analytics Visualization All In One For Dummies
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Author : Jack A. Hyman
language : en
Publisher: John Wiley & Sons
Release Date : 2024-03-05
Data Analytics Visualization All In One For Dummies written by Jack A. Hyman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-05 with Computers categories.
Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sources Organize and analyze data Use data to tell a story with Tableau Expand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off.
Power Bi Data Modeling
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Author : Nisal Mihiranga
language : en
Publisher: BPB Publications
Release Date : 2022-03-22
Power Bi Data Modeling written by Nisal Mihiranga and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-22 with Antiques & Collectibles categories.
Build Power BI Models Efficiently and Effectively KEY FEATURES ● Extensive examples illustrating Power BI and data modeling concepts. ● Includes graphical images and explanations of using Power BI. ● Numerous hands-on practical examples are teaching best practices in predictive modeling. DESCRIPTION Creating data models has never been straightforward. This book demonstrates how to formulate a complete business analytics model that combines several data sources, executes numerous computations, and scales across hundreds of BI users. To begin, you'll learn about the Microsoft Power BI ecosystem by downloading the Power BI desktop and exploring all of its features and capabilities. Through examples, you'll learn how to connect to databases of Excel; and SQL Server, shaping the data with Power Query, and then transforming the data into actionable information. You will gain knowledge of the DAX language by exploring it, writing DAX functions, and creating hierarchies. You will be trained to develop effective business intelligence models by studying numerous data modeling topics. You get to put professionals' best practices to the test when handling large data scenarios and executing analytics on top of them. Additionally, the book discusses how to scale Power BI while considering its storage, memory, and security requirements. You'll see that several new topics have been included, including performance tuning, DAX Studio, sharing Power BI reports, and publishing reports to Sharepoint online. WHAT YOU WILL LEARN ● Conduct profiling, cleansing, and transformation of data. ● Build data models, aggregate data, and create hierarchies. ● Practice DAX language, write calculations, and execute them. ● Utilize advanced features including AI visualizations and performance analyzer. ● Examine various connection types and connect data from different sources. ● Enhance performance by boosting storage and memory. WHO THIS BOOK IS FOR This book is intended for data analysts, business analysts, and any other business user who are interested in learning how to develop data models using Power BI from beginning to end. To follow this book and master Power BI, a basic understanding of data visualization would be sufficient. TABLE OF CONTENTS 1. Introduction to Microsoft Power BI 2. Microsoft Power BI Eco-system 3. Getting Started with Power BI and Connect with Data 4. My first Power BI Report 5. Intro to BI Building Blocks & Dimensional Mod Concepts 6. Get Data from Relational Databases 7. Cleansing, Blending and Transform Data using Power Query 8. Build Relationships 9. Introduction to DAX and Calculated Columns, Cal Measures & Hierarchies 10. Create Insightful Visuals 11. Row-level Security 12. Calculation Groups in Power BI 13. Self-service AI in Power BI 14. Incremental Refresh for Scalable Models 15. Composite Models & Implement Aggregations to Improve query performance 16. Self-service Data Prep for Any Data 17. Optimize DAX 18. Collaborate Your Power BI Workload 19. Performance Tuning via optimizing Storage and Memory
Database Modeling Step By Step
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Author : Gavin Powell
language : en
Publisher: CRC Press
Release Date : 2020-01-06
Database Modeling Step By Step written by Gavin Powell and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-06 with Computers categories.
With the aim of simplifying relational database modeling, Database Modeling Step-by-Step presents the standard approach to database normalization and then adds its own approach, which is a more simplistic, intuitive way to building relational database models. Going from basics to contemporary topics, the book opens with relational data modeling and ends with BigData database modeling following a road map of the evolution in relational modeling and including brief introductions to data warehousing and BigData modeling. A break-down of the elements of a model explains what makes up a relational data model. This is followed by a comparison between standard normalization and a more simplistic intuitive approach to data modeling that a beginner can follow and understand. A brief chapter explains how to use the database programming language SQL (Structured Query Language), which reads from and writes to a relational database. SQL is fundamental to data modeling because it helps in understanding how the model is used. In addition to the relational model, the last three chapters cover important modern world topics including denormalization that leads into data warehouses and BigData database modeling. The book explains how there is not much to logical data modeling in BigData databases because as they are often schema-less, which means that BigData databases do not have schemas embedded into the database itself, they have no metadata and thus not much of a logical data model. Online bonus chapters include a case study that covers relational data modeling and are available at the author’s web site: www.oracletroubleshooter.com/datamodeling.html
Artificial Intelligent Tools
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Author : Yunus Topsakal
language : en
Publisher: Yunus Topsakal
Release Date : 2024-11-19
Artificial Intelligent Tools written by Yunus Topsakal and has been published by Yunus Topsakal this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-19 with Biography & Autobiography categories.
This book serves as a comprehensive guide for readers who wish to understand how artificial intelligence works, how it is used, and which fields it serves with concrete examples, covering a total of 156 fundamental AI tools across 12 main categories and 49 subcategories. These tools, starting with major categories such as natural language processing, image processing, data analytics, and robotic systems, offer groundbreaking solutions in the world of information technologies with their functionality and versatility. The tools presented in this book aim to enhance the readers' academic knowledge and practical application skills by offering innovative and effective solutions in various fields. Each tool is introduced according to the fundamental principles of its respective area, with technical explanations and usage scenarios on how it works. The content of the book is designed to be beneficial to a wide audience, ranging from researchers to students, software developers to industry professionals. Each chapter of the book is detailed to ensure an in-depth understanding of artificial intelligence. Examples demonstrating the application areas, benefits, and limitations of each tool allow the reader to assimilate the information with a practical approach. We hope that this book will serve as a reference source for all readers who wish to explore innovative solutions in AI and gain deep knowledge in this field.
Data Architecture A Primer For The Data Scientist
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Author : W.H. Inmon
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-11-26
Data Architecture A Primer For The Data Scientist written by W.H. Inmon and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-26 with Computers categories.
Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You'll be able to: - Turn textual information into a form that can be analyzed by standard tools. - Make the connection between analytics and Big Data - Understand how Big Data fits within an existing systems environment - Conduct analytics on repetitive and non-repetitive data - Discusses the value in Big Data that is often overlooked, non-repetitive data, and why there is significant business value in using it - Shows how to turn textual information into a form that can be analyzed by standard tools - Explains how Big Data fits within an existing systems environment - Presents new opportunities that are afforded by the advent of Big Data - Demystifies the murky waters of repetitive and non-repetitive data in Big Data
2021 International Conference On Big Data Analytics For Cyber Physical System In Smart City
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Author : Mohammed Atiquzzaman
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
2021 International Conference On Big Data Analytics For Cyber Physical System In Smart City written by Mohammed Atiquzzaman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.
This book gathers a selection of peer-reviewed papers presented at the third Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021) conference, held in Shanghai, China, on Nov. 27, 2021. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
A Friendly Guide To Data Science
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Author : Kelly P. Vincent
language : en
Publisher: Springer Nature
Release Date : 2025-06-26
A Friendly Guide To Data Science written by Kelly P. Vincent and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-26 with Computers categories.
Unlock the world of data science—no coding required. Curious about data science but not sure where to start? This book is a beginner-friendly guide to what data science is and how people use it. It walks you through the essential topics—what data analysis involves, which skills are useful, and how terms like “data analytics” and “machine learning” connect—without getting too technical too fast. Data science isn’t just about crunching numbers, pulling data from a database, or running fancy algorithms. It’s about asking the right questions, understanding the process from start to finish, and knowing what’s possible (and what’s not). This book teaches you all of that, while also introducing important topics like ethics, privacy, and security—because working with data means thinking about people, too. Whether you're a student exploring new skills, a professional navigating data-driven decisions, or someone considering a career change, this book is your friendly gateway into the world of data science, one of today’s most exciting fields. No coding or programming experience? No problem. You'll build a solid foundation and gain the confidence to engage with data science concepts— just as AI and data become increasingly central to everyday life. What You Will Learn Grasp foundational statistics and how it matters in data analysis and data science Understand the data science project life cycle and how to manage a data science project Examine the ethics of working with data and its use in data analysis and data science Understand the foundations of data security and privacy Collect, store, prepare, visualize, and present data Identify the many types of machine learning and know how to gauge performance Prepare for and find a career in data science Who This Book is for A wide range of readers who are curious about data science and eager to build a strong foundation. Perfect for undergraduates in the early semesters of their data science degrees, as it assumes no prior programming or industry experience. Professionals will find particular value in the real-world insights shared through practitioner interviews. Business leaders can use it to better understand what data science can do for them and how their teams are applying it. And for career changers, this book offers a welcoming entry point into the field—helping them explore the landscape before committing to more intensive learning paths like degrees or boot camps.