Data Modeling For The Business
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Data Modeling For The Business
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Author : Steve Hoberman
language : en
Publisher: Technics Publications Llc
Release Date : 2009
Data Modeling For The Business written by Steve Hoberman and has been published by Technics Publications Llc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.
Did you ever try getting Business and IT to agree on the project scope for a new application? Or try getting the Sales & Marketing department to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse -- without them dozing off? You can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives. Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach. Know how to evaluate toolsets for building and storing your models. Practice exercises and walk through a case study to reinforce your modelling skills.
Logical Data Modeling
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Author : Alan Chmura
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-09-29
Logical Data Modeling written by Alan Chmura and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-09-29 with Computers categories.
Logical Data Modeling offers business managers, analysts, and students a clear, basic systematic guide to defining business information structures in relational database terms. The approach, based on Clive Finkelstein’s business-side Information Engineering, is hands-on, practical, and explicit in terminology and reasoning. Filled with illustrations, examples, and exercises, Logical Data Modeling makes its subject accessible to readers with only a limited knowledge of database systems. The book covers all essential topics thoroughly but succinctly: entities, associations, attributes, keys and inheritance, valid and invalid structures, and normalization. It also emphasizes communication with business and database specialists, documentation, and the use of Visible Systems' Visible Advantage enterprise modeling tool. The application of design patterns to logical data modeling provides practitioners with a practical tool for fast development. At the end, a chapter covers the issues that arise when the logical data model is translated into the design for a physical database.
Data Modeling Made Simple
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Author : Steve Hoberman
language : en
Publisher: Technics Publications, LLC
Release Date : 2005
Data Modeling Made Simple written by Steve Hoberman and has been published by Technics Publications, LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
Ever have a bad data day? If you are a business user, architect, analyst, designer or developer, then you have probably had some bad data days. It comes with the territory. Overcoming these problems is much easier if you have an in-depth understanding of the actual data. That's where a data model comes in handy. It's a diagram that uses text and symbols to represent groupings of data, giving you a clear picture of your business and application environment. The book provides the tools you need to read, create and validate models of your business and applications. Contains everything about modelling you need to know but were too afraid to ask, such as: What are the traditional and non-traditional uses of a data model? How do subject area, logical, and physical data models differ? When do I build a BSAM, ASAM, or CSAM? What is the easiest way to apply normalisation? Where can I best leverage abstraction? How do I decide whether to use denormalisation or dimensionality? What are primary, foreign, alternate, virtual, and surrogate keys? What is the best approach to building the models? How can I use the Scorecard system to validate a data model? Includes over 30 exercises to reinforce concepts and sharpen your skills!
Data Modeling For Quality
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Author : Graham Witt
language : en
Publisher: Technics Publications
Release Date : 2021-01-20
Data Modeling For Quality written by Graham Witt and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-20 with categories.
This book is for all data modelers, data architects, and database designers―be they novices who want to learn what's involved in data modeling, or experienced modelers who want to brush up their skills. A novice will not only gain an overview of data modeling, they will also learn how to follow the data modeling process, including the activities required for each step. The experienced practitioner will discover (or rediscover) techniques to ensure that data models accurately reflect business requirements. This book describes rigorous yet easily implemented approaches to: modeling of business information requirements for review by business stakeholders before development of the logical data model normalizing data, based on simple questions rather than the formal definitions which many modelers find intimidating naming and defining concepts and attributes modeling of time-variant data documenting business rules governing both the real world and data data modeling in an Agile project managing data model change in any type of project transforming a business information model to a logical data model against which developers can code implementing the logical data model in a traditional relational DBMS, an SQL:2003-compliant DBMS, an object-relational DBMS, or in XML. Part 1 describes business information models in-depth, including: the importance of modeling business information requirements before embarking on a logical data model business concepts (entity classes) attributes of business concepts attribute classes as an alternative to DBMS data types relationships between business concepts time-variant data generalization and specialization of business concepts naming and defining the components of the business information model business rules governing data, including a distinction between real-world rules and data rules. Part 2 journeys from requirements to a working data resource, covering: sourcing data requirements developing the business information model communicating it to business stakeholders for review, both as diagrams and verbally managing data model change transforming the business information model into a logical data model of stored data for implementation in a relational or object-relational DBMS attribute value representation and data constraints (important but often overlooked) modeling data vault, dimensional and XML data.
Information Structure Design For Databases
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Author : Andrew J. Mortimer
language : en
Publisher: Butterworth-Heinemann
Release Date : 2014-05-12
Information Structure Design For Databases written by Andrew J. Mortimer and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-12 with Computers categories.
Computer Weekly Professional Series: Information Structure Design for Databases: A Practical Guide to Data modeling focuses on practical data modeling covering business and information systems. The publication first offers information on data and information, business analysis, and entity relationship model basics. Discussions cover degree of relationship symbols, relationship rules, membership markers, types of information systems, data driven systems, cost and value of information, importance of data modeling, and quality of information. The book then takes a look at entity relationship modeling connections, one-to-one relationship, and entity relationship modeling advanced topics, including connection traps, resolving many-to-many relationships, four combinations of membership, and entity merging. The text examines logical data dictionary, data flow diagrams, entity life history, and developing database applications. Topics include data modeling during development, waterfall approach, iterative development, sequence, selection, illegal data flow linkages, conservation of data, second normal form rule, and denormalization. The book is a valuable reference for researchers interested in data modeling.
Expert Data Modeling With Power Bi
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Author : Soheil Bakhshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-04-28
Expert Data Modeling With Power Bi written by Soheil Bakhshi 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 2023-04-28 with Computers categories.
Take your Power BI reports to the next level by learning various data modeling techniques and leveraging the latest features of Power BI effectively Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Get an understanding of data modeling techniques using Power BI with this up-to-date guide Learn how to define the relationships between data sets to extract valuable insights Explore best practices for data preparation and modeling and build optimal data models to solve a wide variety of real-world business challenges Book DescriptionThis book is a comprehensive guide to understanding the ins and outs of data modeling and how to create full-fledged data models using Power BI confidently. In this new, fully updated edition, 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. As you advance through the chapters, the book will demonstrate how to prepare efficient data models in the Power Query Editor and use simpler DAX code with new data modeling features. You'll explore how to use the various data modeling and navigation techniques and perform custom calculations using the modeling features with the help of real-world examples. 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. Additionally, you'll learn valuable best practices and explore common data modeling complications and the solutions to supercharge the process of creating a data model in Power BI and build better-performing data models. 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 high-performing reports and data analytics.What you will learn 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 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 calculation groups, aggregations, incremental refresh, RLS/OLS, and more Get well-versed with datamarts and dataflows in PowerBI Who this book is for This MS Power BI book is for BI users, data analysts, and analysis developers who want to become well-versed with data modeling techniques to make the most of Power BI. Basic working knowledge of Power BI and the Star Schema functionality are required to help you to understand the concepts covered in this book.
Data Modeling Essentials
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Author : Graeme C. Simsion
language : en
Publisher:
Release Date : 2001
Data Modeling Essentials written by Graeme C. Simsion and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
This essential guide focuses on data quality and why the data model is so important, plus includes essential material on developing a real model, and covers organization of the modeling task and managing compromises.
Data Modeling Made Simple
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Author : Steve Hoberman
language : en
Publisher: Technics Publications Llc
Release Date : 2009
Data Modeling Made Simple written by Steve Hoberman and has been published by Technics Publications Llc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.
Read today's business headlines and you will see that many issues stem from people not having the right data at the right time. Data issues don't always make the front page, yet they exist within every organisation. We need to improve how we manage data -- and the most valuable tool for explaining, vaildating and managing data is a data model. This book provides the business or IT professional with a practical working knowledge of data modelling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives: Know when a data model is needed and which type of data model is most effective for each situation; Read a data model of any size and complexity with the same confidence as reading a book; Build a fully normalised relational data model, as well as an easily navigatable dimensional model; Apply techniques to turn a logical data model into an efficient physical design; Leverage several templates to make requirements gathering more efficient and accurate; Explain all ten categories of the Data Model Scorecard®; Learn strategies to improve your working relationships with others; Appreciate the impact unstructured data has, and will have, on our data modelling deliverables; Learn basic UML concepts; Put data modelling in context with XML, metadata, and agile development.
Dimensional Modeling In A Business Intelligence Environment
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Author : Chuck Ballard
language : en
Publisher: IBM Redbooks
Release Date : 2012-07-31
Dimensional Modeling In A Business Intelligence Environment written by Chuck Ballard and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-31 with Computers categories.
In this IBM Redbooks publication we describe and demonstrate dimensional data modeling techniques and technology, specifically focused on business intelligence and data warehousing. It is to help the reader understand how to design, maintain, and use a dimensional model for data warehousing that can provide the data access and performance required for business intelligence. Business intelligence is comprised of a data warehousing infrastructure, and a query, analysis, and reporting environment. Here we focus on the data warehousing infrastructure. But only a specific element of it, the data model - which we consider the base building block of the data warehouse. Or, more precisely, the topic of data modeling and its impact on the business and business applications. The objective is not to provide a treatise on dimensional modeling techniques, but to focus at a more practical level. There is technical content for designing and maintaining such an environment, but also business content. For example, we use case studies to demonstrate how dimensional modeling can impact the business intelligence requirements for your business initiatives. In addition, we provide a detailed discussion on the query aspects of BI and data modeling. For example, we discuss query optimization and how you can determine performance of the data model prior to implementation. You need a solid base for your data warehousing infrastructure . . . . a solid data model.
Data Modeling Overview For Managers And Business Analysts
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Author : Bill Inmon
language : en
Publisher:
Release Date : 2017
Data Modeling Overview For Managers And Business Analysts written by Bill Inmon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Bill explains to a manager and business analyst audience the basics of data modeling. The concept of a data model is explained, its benefits and the different layers of data models. Bill covers: Data Model Overview. Bill provides a management's perspective to data modeling. Bill talks about how the data model can help us go from chaos into an organized world. Bill explains what the data model is and covers the three levels of modeling. He covers the process of going from the model to database design. Importance of the Data Model . Bill explains why the data model is an invaluable map and compass of an organization's data. The rules of data model are covered along with how the data model is used within a data warehouse. The data model's role in source/target mapping is also discussed. Generic Data Models . A bank scenario is used to explain the value of leveraging industry-wide generic data models. Len Silverston's models are introduced as well. Bill shares words of caution on using generic models, such as the amount of customization that may be needed to make it useable within your organization. Both operational and analytical generic models are discussed. Data Model Mappings . Bill discusses the process of getting legacy data into a data warehouse using the data model and mapping to the data model. Bill provides the criteria for choosing an appropriate data source for the data warehouse. Data Model Mechanics . The three levels of data models are discussed: high, medium, and low level. The high level is called the entity level, the medium is called the data item set (DIS) level, and the low level is called the physical design level. Bill explains the differences between atomic and derived data. He goes into detail into each of the three levels of data models, and talks about the benefits of each level. Characteristics at the physical level are covered, such as indexing and denormalization.