Model And Data Engineering

Author : Jesse Anderson
Publisher : Unknown
Page : 128 pages
File Size : 47,7 Mb
Release : 2020
Category : Electronic
ISBN : 1484262298

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Data Teams by Jesse Anderson Pdf

Author : Kent Graziano
Publisher : Unknown
Page : 50 pages
File Size : 42,7 Mb
Release : 2015-11-22
Category : Electronic
ISBN : 1796584932

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An Introduction to Agile Data Engineering Using Data Vault 2. 0 by Kent Graziano Pdf

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.

Author : Vlad Riscutia
Publisher : Simon and Schuster
Page : 334 pages
File Size : 41,9 Mb
Release : 2021-08-17
Category : Computers
ISBN : 9781617298929

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Data Engineering on Azure by Vlad Riscutia Pdf

Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure. Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data

Author : Steven L. Brunton,J. Nathan Kutz
Publisher : Cambridge University Press
Page : 615 pages
File Size : 40,9 Mb
Release : 2022-05-05
Category : Computers
ISBN : 9781009098489

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Data-Driven Science and Engineering by Steven L. Brunton,J. Nathan Kutz Pdf

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Author : Ralph Kimball,Margy Ross
Publisher : John Wiley & Sons
Page : 464 pages
File Size : 42,6 Mb
Release : 2011-08-08
Category : Computers
ISBN : 9781118082140

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The Data Warehouse Toolkit by Ralph Kimball,Margy Ross Pdf

This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.

Author : James Densmore
Publisher : O'Reilly Media
Page : 277 pages
File Size : 48,9 Mb
Release : 2021-02-10
Category : Computers
ISBN : 9781492087809

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Data Pipelines Pocket Reference by James Densmore Pdf

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting

Author : Brian Shive
Publisher : Technics Publications
Page : 0 pages
File Size : 53,7 Mb
Release : 2013
Category : Computers
ISBN : 1935504606

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Data Engineering by Brian Shive Pdf

If you found a rusty old lamp on the beach, and upon touching it a genie appeared and granted you three wishes, what would you wish for? If you were wishing for a successful application development effort, most likely you would wish for accurate and robust data models, comprehensive data flow diagrams, and an acute understanding of human behavior. The wish for well-designed conceptual and logical data models means the requirements are well-understood and that the design has been built with flexibility and extensibility leading to high application agility and low maintenance costs. The wish for detailed data flow diagrams means a concrete understanding of the business' value chain exists and is documented. The wish to understand how we think means excellent team dynamics while analyzing, designing, and building the application. Why search the beaches for genie lamps when instead you can read this book? Learn the skills required for modeling, value chain analysis, and team dynamics by following the journey the author and son go through in establishing a profitable summer lemonade business. This business grew from season to season proportionately with his adoption of important engineering principles. All of the concepts and principles are explained in a novel format, so you will learn the important messages while enjoying the story that unfolds within these pages. The story is about an old man who has spent his life designing data models and databases and his newly adopted son. Father and son have a 54 year age difference that produces a large generation gap. The father attempts to narrow the generation gap by having his nine-year-old son earn his entertainment money. The son must run a summer business that turns a lemon grove into profits so he can buy new computers and games. As the son struggles for profits, it becomes increasingly clear that dad's career in information technology can provide critical leverage in achieving success in business. The failures and successes of the son's business over the summers are a microcosm of the ups and downs of many enterprises as they struggle to manage information technology.

Author : Paul Crickard
Publisher : Packt Publishing Ltd
Page : 357 pages
File Size : 50,7 Mb
Release : 2020-10-23
Category : Computers
ISBN : 9781839212307

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Data Engineering with Python by Paul Crickard Pdf

Build, monitor, and manage real-time data pipelines to create data engineering infrastructure efficiently using open-source Apache projects Key Features Become well-versed in data architectures, data preparation, and data optimization skills with the help of practical examples Design data models and learn how to extract, transform, and load (ETL) data using Python Schedule, automate, and monitor complex data pipelines in production Book DescriptionData engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.What you will learn Understand how data engineering supports data science workflows Discover how to extract data from files and databases and then clean, transform, and enrich it Configure processors for handling different file formats as well as both relational and NoSQL databases Find out how to implement a data pipeline and dashboard to visualize results Use staging and validation to check data before landing in the warehouse Build real-time pipelines with staging areas that perform validation and handle failures Get to grips with deploying pipelines in the production environment Who this book is for This book is for data analysts, ETL developers, and anyone looking to get started with or transition to the field of data engineering or refresh their knowledge of data engineering using Python. This book will also be useful for students planning to build a career in data engineering or IT professionals preparing for a transition. No previous knowledge of data engineering is required.

Author : Christian Attiogbé,Sadok Ben Yahia
Publisher : Springer Nature
Page : 329 pages
File Size : 40,8 Mb
Release : 2021-06-14
Category : Computers
ISBN : 9783030784287

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Model and Data Engineering by Christian Attiogbé,Sadok Ben Yahia Pdf

This book constitutes the refereed proceedings of the 10th International Conference on Model and Data Engineering, MEDI 2021, held in Tallinn, Estonia, in June 2021. The 16 full papers and 8 short papers presented in this book were carefully reviewed and selected from 47 submissions. Additionally, the volume includes 3 abstracts of invited talks. The papers cover broad research areas on both theoretical, systems and practical aspects. Some papers include mining complex databases, concurrent systems, machine learning, swarm optimization, query processing, semantic web, graph databases, formal methods, model-driven engineering, blockchain, cyber physical systems, IoT applications, and smart systems. Due to the Corona pandemic the conference was held virtually.

Author : Ladjel Bellatreche,George Chernishev,Antonio Corral,Samir Ouchani,Jüri Vain
Publisher : Springer Nature
Page : 337 pages
File Size : 45,5 Mb
Release : 2021-10-06
Category : Computers
ISBN : 9783030876579

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Advances in Model and Data Engineering in the Digitalization Era by Ladjel Bellatreche,George Chernishev,Antonio Corral,Samir Ouchani,Jüri Vain Pdf

This book constitutes the thoroughly refereed papers of the workshops held at the 10th International Conference on New Trends in Model and Data Engineering, MEDI 2021, held in Tallinn, Estonia, in June 2021: Workshop on moDeling, vErification and Testing of dEpendable CriTical systems, DETECT 2021; Symposium on Intelligent and Autonomous Systems, SIAS 2021; Worjshop on Control Software: Methods, Models, and Languages, CSMML 2021; Blockchain for Inter-Organizational Collaboration, BIOC 2021; The International Health Data Workshop, HEDA 2021. The 20 full and the 4 short workshop papers presented were carefully reviewed and selected from 61 submissions. The papers are organized according to the workshops: Workshop on moDeling, vErification and Testing of dEpendable CriTical systems, DETECT 2021; Symposium on Intelligent and Autonomous Systems, SIAS 2021; Worjshop on Control Software: Methods, Models, and Languages, CSMML 2021; Blockchain for Inter-Organizational Collaboration, BIOC 2021; The International Health Data Workshop, HEDA 2021.

Author : Philippe Fournier-Viger,Ahmed Hassan,Ladjel Bellatreche,Ahmed Awad,Abderrahim Ait Wakrime,Yassine Ouhammou,Idir Ait Sadoune
Publisher : Springer Nature
Page : 227 pages
File Size : 46,6 Mb
Release : 2023-01-09
Category : Computers
ISBN : 9783031231193

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Advances in Model and Data Engineering in the Digitalization Era by Philippe Fournier-Viger,Ahmed Hassan,Ladjel Bellatreche,Ahmed Awad,Abderrahim Ait Wakrime,Yassine Ouhammou,Idir Ait Sadoune Pdf

This volume constitutes short papers and DETECT 2022 workshop papers, presented during the 11th International Conference on Model and Data Engineering, MEDI 2022, held in Cairo, Egypt, in November 2022. The 11 short papers presented were selected from the total of 65 submissions. This volume also contains the 4 accepted papers from the DETECT 2022 workshop, held at MEDI 2022. The volume focuses on advances in data management and modelling, including topics such as data models, data processing, database theory, database systems technology, and advanced database applications.

Author : Mohamed Mosbah,Tahar Kechadi,Ladjel Bellatreche,Faiez Gargouri
Publisher : Springer Nature
Page : 399 pages
File Size : 54,5 Mb
Release : 2024-01-22
Category : Computers
ISBN : 9783031493331

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Model and Data Engineering by Mohamed Mosbah,Tahar Kechadi,Ladjel Bellatreche,Faiez Gargouri Pdf

This volume LNCS 14396 constitutes the refereed proceedings of the 12th International Conference, MEDI 2023,in November 2023 ,held in Sousse, Tunisia. The 27 full papers were carefully peer reviewed and selected from 99 submissions. The Annual International Conference on Model and Data Engineering focuses on bring together researchers and practitioners and enabling them to showcase the latest advances in modelling and data management.

Author : Max Kuhn,Kjell Johnson
Publisher : CRC Press
Page : 266 pages
File Size : 47,8 Mb
Release : 2019-07-25
Category : Business & Economics
ISBN : 9781351609463

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Feature Engineering and Selection by Max Kuhn,Kjell Johnson Pdf

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Author : Tobias Macey
Publisher : "O'Reilly Media, Inc."
Page : 243 pages
File Size : 47,5 Mb
Release : 2021-06-11
Category : Computers
ISBN : 9781492062363

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97 Things Every Data Engineer Should Know by Tobias Macey Pdf

Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail

Author : Joe Reis,Matt Housley
Publisher : "O'Reilly Media, Inc."
Page : 454 pages
File Size : 49,6 Mb
Release : 2022-06-22
Category : Computers
ISBN : 9781098108250

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Fundamentals of Data Engineering by Joe Reis,Matt Housley Pdf

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology. This book will help you: Get a concise overview of the entire data engineering landscape Assess data engineering problems using an end-to-end framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle