Data Modeling Made Simple

Data Modeling Made Simple

Author: Steve Hoberman

Publisher: Technics Publications

ISBN: 9780977140060

Category: Computers

Page: 360

View: 556

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.
Categories: Computers

Data Modeling Made Simple with erwin DM

Data Modeling Made Simple with erwin DM

This book contains seven parts.

Author: Jeff Harris

Publisher: Technics Publications

ISBN: 9781634628464

Category: Computers

Page: 538

View: 446

Master erwin DM to deliver robust and precise designs for both operational and analytical projects. Steve and Jeff start from the basics, explaining data modeling concepts and how to get up and running with erwin DM (erwin DM). Through a hands-on approach, business analysts, data professionals, and project managers will learn step-by-step how to build effective conceptual, logical, and physical data models. Complete the stages in identifying essential business requirements, designing the logical data model, transposing those logical modeling objects into physical tables and columns, and even generating the implementation database scripts. This book contains seven parts. Part I provides a foundation in data modeling and Part II a foundation in erwin DM. Part III covers the design layer technique and its application using erwin DM, distinguishing conceptual, logical, physical, and operational data models. Part IV covers entities, domains, attributes, key groups, validation rules, default rules, and subject areas, along with how to implement them using erwin DM. Part V explains the physical data model and how to convert a logical data model to a physical data model in erwin DM. Become confident creating tables, columns, indexes, and views. Part VI reveals advanced features available within erwin DM, including user defined properties, naming standards, forward engineering, reverse engineering, complete compare, report designer, and the bulk editor. Part VII explains several important tools to use in combination with erwin DM, including erwin DM NoSQL, erwin Data Catalog, and erwin Data Literacy.
Categories: Computers

Data Modeling Made Simple with CA ERwin Data Modeler r8

Data Modeling Made Simple with CA ERwin Data Modeler r8

This book combines real-world experience and best practices with down to earth advice, humor, and even cartoons to help you master the following ten objectives: 1.

Author: Donna Burbank

Publisher: Technics Publications

ISBN: 9781634620697

Category: Computers

Page: 536

View: 753

Data Modeling Made Simple with CA ERwin Data Modeler r8 will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices, and how to apply these principles with CA ERwin Data Modeler r8. You’ll build many CA ERwin data models along the way, mastering first the fundamentals and later in the book the more advanced features of CA ERwin Data Modeler. This book combines real-world experience and best practices with down to earth advice, humor, and even cartoons to help you master the following ten objectives: 1. Understand the basics of data modeling and relational theory, and how to apply these skills using CA ERwin Data Modeler 2. Read a data model of any size and complexity with the same confidence as reading a book 3. Understand the difference between conceptual, logical, and physical models, and how to effectively build these models using CA ERwin’s Data Modelers Design Layer Architecture 4. Apply techniques to turn a logical data model into an efficient physical design and vice-versa through forward and reverse engineering, for both ‘top down’ and bottom-up design 5. Learn how to create reusable domains, naming standards, UDPs, and model templates in CA ERwin Data Modeler to reduce modeling time, improve data quality, and increase enterprise consistency 6. Share data model information with various audiences using model formatting and layout techniques, reporting, and metadata exchange 7. Use the new workspace customization features in CA ERwin Data Modeler r8 to create a workflow suited to your own individual needs 8. Leverage the new Bulk Editing features in CA ERwin Data Modeler r8 for mass metadata updates, as well as import/export with Microsoft Excel 9. Compare and merge model changes using CA ERwin Data Modelers Complete Compare features 10. Optimize the organization and layout of your data models through the use of Subject Areas, Diagrams, Display Themes, and more Section I provides an overview of data modeling: what it is, and why it is needed. The basic features of CA ERwin Data Modeler are introduced with a simple, easy-to-follow example. Section II introduces the basic building blocks of a data model, including entities, relationships, keys, and more. How-to examples using CA ERwin Data Modeler are provided for each of these building blocks, as well as ‘real world’ scenarios for context. Section III covers the creation of reusable standards, and their importance in the organization. From standard data modeling constructs such as domains to CA ERwin-specific features such as UDPs, this section covers step-by-step examples of how to create these standards in CA ERwin Data Modeling, from creation, to template building, to sharing standards with end users through reporting and queries. Section IV discusses conceptual, logical, and physical data models, and provides a comprehensive case study using CA ERwin Data Modeler to show the interrelationships between these models using CA ERwin’s Design Layer Architecture. Real world examples are provided from requirements gathering, to working with business sponsors, to the hands-on nitty-gritty details of building conceptual, logical, and physical data models with CA ERwin Data Modeler r8. From the Foreword by Tom Bilcze, President, CA Technologies Modeling Global User Community: Data Modeling Made Simple with CA ERwin Data Modeler r8 is an excellent resource for the ERwin community. The data modeling community is a diverse collection of data professionals with many perspectives of data modeling and different levels of skill and experience. Steve Hoberman and Donna Burbank guide newbie modelers through the basics of data modeling and CA ERwin r8. Through the liberal use of illustrations, the inexperienced data modeler is graphically walked through the components of data models and how to create them in CA ERwin r8. As an experienced data modeler, Steve and Donna give me a handbook for effectively using the new and enhanced features of this release to bring my art form to life. The book delves into advanced modeling topics and techniques by continuing the liberal use of illustrations. It speaks to the importance of a defined data modeling architecture with soundly modeled data to assist the enterprise in understanding of the value of data. It guides me in applying the finishing touches to my data designs.
Categories: Computers

Data Modeling Made Simple with PowerDesigner

Data Modeling Made Simple with PowerDesigner

This book combines real-world experience and best practices to help you master the following ten objectives: This book has ten key objectives for you, the reader: 1.

Author: Steve Hoberman

Publisher: Technics Publications

ISBN: 9781634620703

Category: Computers

Page: 532

View: 404

Data Modeling Made Simple with PowerDesigner will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices, and how to apply these principles with PowerDesigner. You'll build many PowerDesigner data models along the way, increasing your skills first with the fundamentals and later with more advanced feature of PowerDesigner. This book combines real-world experience and best practices to help you master the following ten objectives: This book has ten key objectives for you, the reader: 1. You will know when a data model is needed and which PowerDesigner models are the most appropriate for each situation 2. You will be able to read a data model of any size and complexity with the same confidence as reading a book 3. You will know when to apply and how to make use of all the key features of PowerDesigner 4. You will be able to build, step-by-step in PowerDesigner, a pyramid of linked data models, including a conceptual data model, a fully normalized relational data model, a physical data model, and an easily navigable dimensional model 5. You will be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design 6. You will improve data governance and modeling consistency within your organization by leveraging features such as PowerDesigner’s reference models, Glossary, domains, and model comparison and model mapping techniques 7. You will know how to utilize dependencies and traceability links to assess the impact of change 8. You will know how to integrate your PowerDesigner models with externally-managed files, including the import and export of data using Excel and Requirements documents 9. You will know where you can take advantage of the entire PowerDesigner model set, to increase the success rate of corporate-wide initiatives such as business intelligence and enterprise resource planning (ERP) 10. You will understand the key differentiators between PowerDesigner and other data modeling tools you may have used before This book contains seven sections: Section I introduces data modeling, along with its purpose and variations. Section II explains all of the components on a data model including entities, data elements, relationships, and keys. Also included is a discussion of the importance of quality names and definitions for your objects. Section III explains the important role of data modeling tools, the key features required of any data modeling tool, and an introduction to the essential features of PowerDesigner. It also describes how to create and manage data modeling objects in PowerDesigner. Section IV introduces the Data Model Pyramid, then dives into the relational and dimensional subject areas, logical, and physical data models, and describes how PowerDesigner supports these models and the connections between them. Section V guides you through the creation of your own Data Model Pyramid. Section VI focuses on additional PowerDesigner features (some of which have already been introduced) that make life easier for data modelers. Learn how to get information into and out of PowerDesigner, and improve the quality of your data models with a cross-reference of key PowerDesigner features with the Data Model Scorecard®. Section VII discusses PowerDesigner topics beyond data modeling, including the XML physical model and the other types of model available in PowerDesigner.
Categories: Computers

Data Modeling Made Simple with ER Studio Data Architect

Data Modeling Made Simple with ER Studio Data Architect

This second edition includes numerous updates and new sections including an overview of ER/Studio’s support for agile development, as well as a description of some of ER/Studio’s newer features for NoSQL, such as MongoDB’s containment ...

Author: Steve Hoberman

Publisher: Technics Publications

ISBN: 9781634620949

Category: Computers

Page: 342

View: 167

Build a working knowledge of data modeling concepts and best practices, along with how to apply these principles with ER/Studio. This second edition includes numerous updates and new sections including an overview of ER/Studio’s support for agile development, as well as a description of some of ER/Studio’s newer features for NoSQL, such as MongoDB’s containment structure.
Categories: Computers

Data Modeling Made Simple with Embarcadero ER Studio Data Architect

Data Modeling Made Simple with Embarcadero ER Studio Data Architect

This book contains four sections: Section I introduces data modeling and the ER/Studio landscape.

Author: Steve Hoberman

Publisher:

ISBN: 1634620925

Category:

Page: 350

View: 922

Build a working knowledge of data modeling concepts and best practices, along with how to apply these principles with ER/Studio. This second edition includes numerous updates and new sections including an overview of ER/Studio's support for agile development, as well as a description of some of ER/Studio's newer features for NoSQL, such as MongoDB's containment structure. You will build many ER/Studio data models along the way, applying best practices to master these ten objectives: 1.Know why a data model is needed and which ER/Studio models are the most appropriate for each situation 2.Understand each component on the data model and how to represent and create them in ER/Studio 3.Know how to leverage ER/Studio's latest features including those assisting agile teams and forward and reverse engineering of NoSQL databases 4.Know how to apply all the foundational features of ER/Studio 5.Be able to build relational and dimensional conceptual, logical, and physical data models in ER/Studio 6.Be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design 7.Improve data model quality and impact analysis results by leveraging ER/Studio's lineage functionality and compare/merge utility 8.Be able to apply ER/Studio's data dictionary features 9.Learn ways of sharing the data model through reporting and through exporting the model in a variety of formats 10.Leverage ER/Studio's naming functionality to improve naming consistency, including the new Automatic Naming Translation feature. This book contains four sections: Section I introduces data modeling and the ER/Studio landscape. Learn why data modeling is so critical to software development and even more importantly, why data modeling is so critical to understanding the business. You will learn about the newest features in ER/Studio (including features on big data and agile), and the ER/Studio environment. By the end of this sectio
Categories:

Data Modeling for the Business

Data Modeling for the Business

Did you ever try getting Business and IT to agree on the project scope for a new application?

Author: Steve Hoberman

Publisher: Technics Publications Llc

ISBN: 0977140075

Category: Computers

Page: 285

View: 320

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.
Categories: Computers

THE DATA MODEL RESOURCE BOOK UNIVERSAL PATTERNS FOR DATA MODELING

THE DATA MODEL RESOURCE BOOK  UNIVERSAL PATTERNS FOR DATA MODELING

Market_Desc: · Database administrators· Data Modelers and Analysts· Database Designers Special Features: · The author is a widely known and respected authority on data modeling; he will actively promote the book in writing and speaking ...

Author: Len Silverston

Publisher: John Wiley & Sons

ISBN: 8126519789

Category: Data warehousing

Page: 640

View: 392

Market_Desc: · Database administrators· Data Modelers and Analysts· Database Designers Special Features: · The author is a widely known and respected authority on data modeling; he will actively promote the book in writing and speaking engagements.· Wiley is the leading publisher of books on databases and data warehousing. About The Book: The Data Model Resource Book, Volume 3, presents a collection of common patterns that can be used to customize existing data models (including those in Volumes 1 and 2) as well as create new data models. Each chapter describes a universal data pattern which is applicable across a wide variety of organizations, and includes several examples of specific implementations. The authors also provide more general guidelines and best practices for implementing these patterns, and in particular how to customize existing models as well as convert models into physical database designs.
Categories: Data warehousing

Data Modeling Master Class Training Manual 5th Edition

Data Modeling Master Class Training Manual 5th Edition

This is the fifth edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes.

Author: Steve Hoberman

Publisher:

ISBN: 1935504886

Category: Computers

Page: 328

View: 851

This is the fifth edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes. This text can be purchased prior to attending the Master Class, the latest course schedule and detailed description can be found on Steve Hoberman's website, stevehoberman.com.The Master Class is a complete data modeling course, containing three days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL data models. After learning the styles and steps in capturing and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard®. You will know not just how to build a data model, but how to build a data model well. Two case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects.
Categories: Computers

Data Modeling Master Class Training Manual

Data Modeling Master Class Training Manual

This is the eighth edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes.

Author: Steve Hoberman

Publisher:

ISBN: 1634622111

Category:

Page: 332

View: 906

This is the eighth edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes. This text can be purchased prior to attending the Master Class, the latest course schedule and detailed description can be found on Steve Hoberman's website, stevehoberman.com. The Master Class is a complete data modeling course, containing three days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL data models. After learning the styles and steps in capturing and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard(R). You will know not just how to build a data model, but how to build a data model well. Three case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects. Top 5 Objectives Determine how and when to use each data modeling component Apply techniques to elicit data requirements as a prerequisite to building a data model Build relational and dimensional conceptual, logical, and physical data models Incorporate supportability and extensibility features into the data model Assess the quality of a data model.
Categories:

Data Model Scorecard

Data Model Scorecard

This book, written for people who build, use, or review data models, contains the Data Model Scorecard template and an explanation along with many examples of each of the ten Scorecard categories.

Author: Steve Hoberman

Publisher: Technics Publications

ISBN: 9781634620840

Category: Computers

Page: 202

View: 122

Data models are the main medium used to communicate data requirements from business to IT, and within IT from analysts, modelers, and architects, to database designers and developers. Therefore it’s essential to get the data model right. But how do you determine right? That’s where the Data Model Scorecard® comes in. The Data Model Scorecard is a data model quality scoring tool containing ten categories aimed at improving the quality of your organization’s data models. Many of my consulting assignments are dedicated to applying the Data Model Scorecard to my client’s data models – I will show you how to apply the Scorecard in this book. This book, written for people who build, use, or review data models, contains the Data Model Scorecard template and an explanation along with many examples of each of the ten Scorecard categories. There are three sections: In Section I, Data Modeling and the Need for Validation, receive a short data modeling primer in Chapter 1, understand why it is important to get the data model right in Chapter 2, and learn about the Data Model Scorecard in Chapter 3. In Section II, Data Model Scorecard Categories, we will explain each of the ten categories of the Data Model Scorecard. There are ten chapters in this section, each chapter dedicated to a specific Scorecard category: · Chapter 4: Correctness · Chapter 5: Completeness · Chapter 6: Scheme · Chapter 7: Structure · Chapter 8: Abstraction · Chapter 9: Standards · Chapter 10: Readability · Chapter 11: Definitions · Chapter 12: Consistency · Chapter 13: Data In Section III, Validating Data Models, we will prepare for the model review (Chapter 14), cover tips to help during the model review (Chapter 15), and then review a data model based upon an actual project (Chapter 16).
Categories: Computers

The Rosedata Stone Achieving a Common Business Language using the Business Terms Model

The Rosedata Stone  Achieving a Common Business Language using the Business Terms Model

Creating a precise diagram of business terms within your projects is a simple yet powerful communication tool for project managers, data governance professionals, and business analysts.

Author: Steve Hoberman

Publisher: Technics Publications

ISBN: 9781634627757

Category: Computers

Page: 180

View: 521

Creating a precise diagram of business terms within your projects is a simple yet powerful communication tool for project managers, data governance professionals, and business analysts. Similar to how the Rosetta Stone provided a communication tool across multiple languages, the Rosedata Stone provides a communication tool across business languages. The Rosedata Stone, called the Business Terms Model (BTM) or the Conceptual Data Model, displays the achievement of a Common Business Language of terms for a particular business initiative. With more and more data being created and used, combined with intense competition, strict regulations, and rapid-spread social media, the financial, liability, and credibility stakes have never been higher and therefore the need for a Common Business Language has never been greater. Appreciate the power of the BTM and apply the steps to build a BTM over the book’s five chapters: Challenges. Explore how a Common Business Language is more important than ever with technologies like the Cloud and NoSQL, and Regulations such as the GDPR. Needs. Identify scope and plan precise, minimal visuals that will capture the Common Business Language. Solution. Meet the BTM and its components, along with the variations of relational and dimensional BTMs. Experience how several data modeling tools display the BTM, including CaseTalk, ER/Studio, erwin DM, and Hackolade. Construction. Build operational (relational) and analytics (dimensional) BTMs for a bakery chain. Practice. Reinforce BTM concepts and build BTMs for two of your own initiatives alongside a real example.
Categories: Computers

Handbook for Aligning the Business with Information Technology Using High level Data Models

Handbook for Aligning the Business with Information Technology Using High level Data Models

Author: Steve Hoberman

Publisher: Technics Publications

ISBN: 9780977140077

Category: Computers

Page: 285

View: 991

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.
Categories: Computers

Healthcare Analytics Made Simple

Healthcare Analytics Made Simple

Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.

Author: Vikas (Vik) Kumar

Publisher: Packt Publishing Ltd

ISBN: 9781787283220

Category: Computers

Page: 268

View: 434

Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python and SQL Build predictive models on real healthcare data with pandas and scikit-learn Use analytics to improve healthcare performance Book Description In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples. What you will learn Gain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processes Use SQL and Python to analyze data Measure healthcare quality and provider performance Identify features and attributes to build successful healthcare models Build predictive models using real-world healthcare data Become an expert in predictive modeling with structured clinical data See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.
Categories: Computers

Project Management Made Simple

Project Management Made Simple

Author: David King

Publisher: Prentice Hall

ISBN: 0137177291

Category: Computers

Page: 112

View: 689

Whether you're a professional systems development project manager, or simply aspiring to enter this challenging field, this compact book is all you need! Complete with checklists, progress reports, and questions with answers, it's a practical, hands-on project management 'cookbook' of useful techniques, information, and recommendations that can be used as a daily reference manual as well as a 'dictionary' for the vast database of project management information available.
Categories: Computers

Graph Database Modeling

Graph Database Modeling

This book is designed to walk you through the graph data modeling.

Author: Kanika Thakur

Publisher:

ISBN: 9798679030763

Category:

Page: 60

View: 132

This book is designed to walk you through the graph data modeling. You will be introduced to the basic process of designing a graph data model that can answer a wide range of business questions across a variety of domains. Anyone can do basic data modeling, and with the advent of graph database technology, matching your data to a coherent model is easier than ever.Data modeling is an abstraction process. You start with your business and user needs (i.e., what you want your application to do). Then, in the modeling process you map those needs into a structure for storing and organizing your data. Every data model is unique, depending on the use case and the types of questions that users need to answer with the data. Because of this, there is no "one-size-fits-all" approach to data modeling. Using best practices and careful modeling will provide the most valuable result in producing an accurate data model that benefits your processes and use case. This book is simply the introduction to data modeling using a simple, straightforward scenario. There are plenty of opportunities throughout the upcoming guides to practice modeling domains and analyzing changes to the model that might need to be made. Simply In Depth..........
Categories:

Software Engineering A Practitioner s Approach

Software Engineering  A Practitioner s Approach

[ Hil08 ) Hillside.net , Patterns Catalog , 2008 , available at http://hillside.net/
patterns/ onlinepatterncatalog.htm . [ Hob06 ] Hoberman , S. , Data Modeling
Made Simple , Technics Publications , 2006 . ( Hofooj Hofmeister , C. , R. Nord ,
and D.

Author: Roger S. Pressman

Publisher: McGraw-Hill Science, Engineering & Mathematics

ISBN: UCSD:31822037170040

Category: Computers

Page: 895

View: 676

For over 20 years, this has been the best-selling guide to software engineering for students and industry professionals alike. This seventh edition features a new part four on web engineering, which presents a complete engineering approach for the analysis, design and testing of web applications.
Categories: Computers

Spark The Definitive Guide

Spark  The Definitive Guide

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework.

Author: Bill Chambers

Publisher: "O'Reilly Media, Inc."

ISBN: 9781491912300

Category: COMPUTERS

Page: 608

View: 190

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Spark’s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation
Categories: COMPUTERS

Blockchainopoly

Blockchainopoly

How Blockchain Changes the Rules of the Game

Author: Steve Hoberman

Publisher: Technics Publications

ISBN: 9781634623469

Category: Business & Economics

Page: 226

View: 996

How Blockchain Changes the Rules of the Game
Categories: Business & Economics

Reading Ability of Latvian Students

Reading Ability of Latvian Students

With this technique it is possible to build two level models to describe , explain or
account for the empirical data on both the student , class or school levels . With
this ... ( STREAMS - Structural Equation Modeling Made Simple ) . 6 Arbuckle , J .
L ...

Author: Indra Dedze

Publisher: Institute of International Education Stockholm University

ISBN: STANFORD:36105110948044

Category: Reading

Page: 167

View: 255

Categories: Reading