Data Management at Scale

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492054739
Total Pages : 404 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Data Management at Scale by : Piethein Strengholt

Download or read book Data Management at Scale written by Piethein Strengholt and published by "O'Reilly Media, Inc.". This book was released on 2020-07-29 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

Data Management at Scale

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 109813883X
Total Pages : 412 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Data Management at Scale by : Piethein Strengholt

Download or read book Data Management at Scale written by Piethein Strengholt and published by "O'Reilly Media, Inc.". This book was released on 2023-04-10 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: As data management continues to evolve rapidly, managing all of your data in a central place, such as a data warehouse, is no longer scalable. Today's world is about quickly turning data into value. This requires a paradigm shift in the way we federate responsibilities, manage data, and make it available to others. With this practical book, you'll learn how to design a next-gen data architecture that takes into account the scale you need for your organization. Executives, architects and engineers, analytics teams, and compliance and governance staff will learn how to build a next-gen data landscape. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including regulatory requirements, privacy concerns, and new developments such as data mesh and data fabric Go deep into building a modern data architecture, including cloud data landing zones, domain-driven design, data product design, and more Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

Data Management at Scale

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Author :
Publisher : O'Reilly Media
ISBN 13 : 1492054755
Total Pages : 348 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Data Management at Scale by : Piethein Strengholt

Download or read book Data Management at Scale written by Piethein Strengholt and published by O'Reilly Media. This book was released on 2020-07-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

Web-Scale Data Management for the Cloud

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Publisher : Springer Science & Business Media
ISBN 13 : 1461468566
Total Pages : 209 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Web-Scale Data Management for the Cloud by : Wolfgang Lehner

Download or read book Web-Scale Data Management for the Cloud written by Wolfgang Lehner and published by Springer Science & Business Media. This book was released on 2013-04-06 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: The efficient management of a consistent and integrated database is a central task in modern IT and highly relevant for science and industry. Hardly any critical enterprise solution comes without any functionality for managing data in its different forms. Web-Scale Data Management for the Cloud addresses fundamental challenges posed by the need and desire to provide database functionality in the context of the Database as a Service (DBaaS) paradigm for database outsourcing. This book also discusses the motivation of the new paradigm of cloud computing, and its impact to data outsourcing and service-oriented computing in data-intensive applications. Techniques with respect to the support in the current cloud environments, major challenges, and future trends are covered in the last section of this book. A survey addressing the techniques and special requirements for building database services are provided in this book as well.

Model Management and Analytics for Large Scale Systems

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Publisher : Academic Press
ISBN 13 : 0128166509
Total Pages : 344 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Model Management and Analytics for Large Scale Systems by : Bedir Tekinerdogan

Download or read book Model Management and Analytics for Large Scale Systems written by Bedir Tekinerdogan and published by Academic Press. This book was released on 2019-09-14 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions

Data Mesh

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492092363
Total Pages : 387 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Data Mesh by : Zhamak Dehghani

Download or read book Data Mesh written by Zhamak Dehghani and published by "O'Reilly Media, Inc.". This book was released on 2022-03-08 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.

Data Governance

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Publisher : Academic Press
ISBN 13 : 0128158328
Total Pages : 352 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Data Governance by : John Ladley

Download or read book Data Governance written by John Ladley and published by Academic Press. This book was released on 2019-11-08 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. Incorporates industry changes, lessons learned and new approaches Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations Includes new case studies which detail real-world situations Explores all of the capabilities an organization must adopt to become data driven Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy Provides up to 75% brand-new content compared to the first edition

Frontiers in Massive Data Analysis

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Publisher : National Academies Press
ISBN 13 : 0309287812
Total Pages : 190 pages
Book Rating : 4.3/5 (92 download)

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Book Synopsis Frontiers in Massive Data Analysis by : National Research Council

Download or read book Frontiers in Massive Data Analysis written by National Research Council and published by National Academies Press. This book was released on 2013-09-03 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale--terabytes and petabytes--is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge--from computer science, statistics, machine learning, and application disciplines--that must be brought to bear to make useful inferences from massive data.

Large Scale and Big Data

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Publisher : CRC Press
ISBN 13 : 1466581506
Total Pages : 640 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Large Scale and Big Data by : Sherif Sakr

Download or read book Large Scale and Big Data written by Sherif Sakr and published by CRC Press. This book was released on 2014-06-25 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book’s second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.

Cloud Data Management

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Publisher : Springer
ISBN 13 : 3319047655
Total Pages : 202 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Cloud Data Management by : Liang Zhao

Download or read book Cloud Data Management written by Liang Zhao and published by Springer. This book was released on 2014-07-08 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: In practice, the design and architecture of a cloud varies among cloud providers. We present a generic evaluation framework for the performance, availability and reliability characteristics of various cloud platforms. We describe a generic benchmark architecture for cloud databases, specifically NoSQL database as a service. It measures the performance of replication delay and monetary cost. Service Level Agreements (SLA) represent the contract which captures the agreed upon guarantees between a service provider and its customers. The specifications of existing service level agreements (SLA) for cloud services are not designed to flexibly handle even relatively straightforward performance and technical requirements of consumer applications. We present a novel approach for SLA-based management of cloud-hosted databases from the consumer perspective and an end-to-end framework for consumer-centric SLA management of cloud-hosted databases. The framework facilitates adaptive and dynamic provisioning of the database tier of the software applications based on application-defined policies for satisfying their own SLA performance requirements, avoiding the cost of any SLA violation and controlling the monetary cost of the allocated computing resources. In this framework, the SLA of the consumer applications are declaratively defined in terms of goals which are subjected to a number of constraints that are specific to the application requirements. The framework continuously monitors the application-defined SLA and automatically triggers the execution of necessary corrective actions (scaling out/in the database tier) when required. The framework is database platform-agnostic, uses virtualization-based database replication mechanisms and requires zero source code changes of the cloud-hosted software applications.

Linked Data Management

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Publisher : CRC Press
ISBN 13 : 1466582413
Total Pages : 566 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Linked Data Management by : Andreas Harth

Download or read book Linked Data Management written by Andreas Harth and published by CRC Press. This book was released on 2016-04-19 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linked Data Management presents techniques for querying and managing Linked Data that is available on today's Web. The book shows how the abundance of Linked Data can serve as fertile ground for research and commercial applications.The text focuses on aspects of managing large-scale collections of Linked Data. It offers a detailed introduction to L

The Self-Service Data Roadmap

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492075205
Total Pages : 297 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis The Self-Service Data Roadmap by : Sandeep Uttamchandani

Download or read book The Self-Service Data Roadmap written by Sandeep Uttamchandani and published by "O'Reilly Media, Inc.". This book was released on 2020-09-10 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks. Most organizations can’t scale data science teams fast enough to keep up with the growing amounts of data to transform. What’s the answer? Self-service data. With this practical book, data engineers, data scientists, and team managers will learn how to build a self-service data science platform that helps anyone in your organization extract insights from data. Sandeep Uttamchandani provides a scorecard to track and address bottlenecks that slow down time to insight across data discovery, transformation, processing, and production. This book bridges the gap between data scientists bottlenecked by engineering realities and data engineers unclear about ways to make self-service work. Build a self-service portal to support data discovery, quality, lineage, and governance Select the best approach for each self-service capability using open source cloud technologies Tailor self-service for the people, processes, and technology maturity of your data platform Implement capabilities to democratize data and reduce time to insight Scale your self-service portal to support a large number of users within your organization

Telling Your Data Story

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Publisher :
ISBN 13 : 9781634628952
Total Pages : 196 pages
Book Rating : 4.6/5 (289 download)

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Book Synopsis Telling Your Data Story by : Scott Taylor

Download or read book Telling Your Data Story written by Scott Taylor and published by . This book was released on 2020-11-15 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Data Whisperer's practical guide to explaining and understanding the strategic value of data management. The need for data management is everywhere across your company. The value of every digitally transformative customer-facing initiative, every data science and analytics-based project, every as-a-service offering, every foray into e-commerce, and every enterprise software implementation is inextricably linked to the successful output of data management efforts. Although it is a simple function of garbage in garbage out, that slogan rarely drives any sustainable executive action. We need to tell a better data story. Data Storytelling is probably the hottest non-technical trend in the technology-related space. But it does not directly support data management because it is focused on analytics or telling stories with data. So, it is time to expand the realm of Data Storytelling to recognize the role of data management by telling stories about data. Learn how to secure stakeholder involvement and executive commitment to fund and support data management as a systematic, consistent, fundamental part of your business. This book is for: Data management leaders trying to explain your value to C-Level and business stakeholders. As a practitioner, you may already know how to fix your data, but your business leaders ignore your advice. When you explain data management to the business, they may nod "yes" on the outside, but they nod off on the inside. Business stakeholders trying to comprehend why data management is important. Many business people may be frightened, threatened, intimidated, or at the very least confused and bewildered by the techno-babble often associated with data-related conversations. If you want to know more about why data management needs to be a strategic imperative in your organization, you'll learn it here in simple terms. Data scientists looking to understand better how you connect to "The Business." A recurring struggle I hear from data scientists is the need to get "closer to business." If you are a data scientist, then you need to understand your company's data story. The more you can align your work to the core value your company delivers, the more successful you will be. This book will help you discover the essence of why data brings value to your business. Anyone interested in understanding the business value of data management. I offer simple explanations about why data management is essential for your organization. Without going deep into technical concepts and processes, I focus on the business-related outputs. I share ways you can think about what foundational data does. Its importance is vital for the future of your enterprise. Since this is a book about telling data stories, I share it through stories divided into five sections: My data story. Why I know what I know and why you should listen to me. Everyone's data story. A collection of classic, foundational data situations relevant to all enterprises. Framing your data story. A set of simple frameworks about data value. Selling your data story. Tips on creating a compelling narrative. Building your data story. Why you must align with the strategic intentions of your enterprise.

The Open Handbook of Linguistic Data Management

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Author :
Publisher : MIT Press
ISBN 13 : 0262045265
Total Pages : 687 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Open Handbook of Linguistic Data Management by : Andrea L. Berez-Kroeker

Download or read book The Open Handbook of Linguistic Data Management written by Andrea L. Berez-Kroeker and published by MIT Press. This book was released on 2022-01-18 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. "Doing language science" depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice. In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involved in data management. Part 2 presents snapshots of practices across various subfields, with each chapter presenting a unique data management project with generalizable guidance for researchers. The Open Handbook of Linguistic Data Management is an essential addition to the toolkit of every linguist, guiding researchers toward making their data FAIR: Findable, Accessible, Interoperable, and Reusable.

Advanced Data Management

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110433079
Total Pages : 374 pages
Book Rating : 4.1/5 (14 download)

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Book Synopsis Advanced Data Management by : Lena Wiese

Download or read book Advanced Data Management written by Lena Wiese and published by Walter de Gruyter GmbH & Co KG. This book was released on 2015-10-29 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced data management has always been at the core of efficient database and information systems. Recent trends like big data and cloud computing have aggravated the need for sophisticated and flexible data storage and processing solutions. This book provides a comprehensive coverage of the principles of data management developed in the last decades with a focus on data structures and query languages. It treats a wealth of different data models and surveys the foundations of structuring, processing, storing and querying data according these models. Starting off with the topic of database design, it further discusses weaknesses of the relational data model, and then proceeds to convey the basics of graph data, tree-structured XML data, key-value pairs and nested, semi-structured JSON data, columnar and record-oriented data as well as object-oriented data. The final chapters round the book off with an analysis of fragmentation, replication and consistency strategies for data management in distributed databases as well as recommendations for handling polyglot persistence in multi-model databases and multi-database architectures. While primarily geared towards students of Master-level courses in Computer Science and related areas, this book may also be of benefit to practitioners looking for a reference book on data modeling and query processing. It provides both theoretical depth and a concise treatment of open source technologies currently on the market.

Practical DataOps

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Publisher : Apress
ISBN 13 : 1484251040
Total Pages : 289 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Practical DataOps by : Harvinder Atwal

Download or read book Practical DataOps written by Harvinder Atwal and published by Apress. This book was released on 2019-12-09 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain a practical introduction to DataOps, a new discipline for delivering data science at scale inspired by practices at companies such as Facebook, Uber, LinkedIn, Twitter, and eBay. Organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into insight-driven action and useful analytical data products. Processes and thinking employed to manage and use data in the 20th century are a bottleneck for working effectively with the variety of data and advanced analytical use cases that organizations have today. This book provides the approach and methods to ensure continuous rapid use of data to create analytical data products and steer decision making. Practical DataOps shows you how to optimize the data supply chain from diverse raw data sources to the final data product, whether the goal is a machine learning model or other data-orientated output. The book provides an approach to eliminate wasted effort and improve collaboration between data producers, data consumers, and the rest of the organization through the adoption of lean thinking and agile software development principles. This book helps you to improve the speed and accuracy of analytical application development through data management and DevOps practices that securely expand data access, and rapidly increase the number of reproducible data products through automation, testing, and integration. The book also shows how to collect feedback and monitor performance to manage and continuously improve your processes and output. What You Will LearnDevelop a data strategy for your organization to help it reach its long-term goals Recognize and eliminate barriers to delivering data to users at scale Work on the right things for the right stakeholders through agile collaboration Create trust in data via rigorous testing and effective data management Build a culture of learning and continuous improvement through monitoring deployments and measuring outcomes Create cross-functional self-organizing teams focused on goals not reporting lines Build robust, trustworthy, data pipelines in support of AI, machine learning, and other analytical data products Who This Book Is For Data science and advanced analytics experts, CIOs, CDOs (chief data officers), chief analytics officers, business analysts, business team leaders, and IT professionals (data engineers, developers, architects, and DBAs) supporting data teams who want to dramatically increase the value their organization derives from data. The book is ideal for data professionals who want to overcome challenges of long delivery time, poor data quality, high maintenance costs, and scaling difficulties in getting data science output and machine learning into customer-facing production.

Scientific Data Management

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Author :
Publisher : Chapman and Hall/CRC
ISBN 13 : 9781420069808
Total Pages : 0 pages
Book Rating : 4.0/5 (698 download)

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Book Synopsis Scientific Data Management by : Arie Shoshani

Download or read book Scientific Data Management written by Arie Shoshani and published by Chapman and Hall/CRC. This book was released on 2009-12-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dealing with the volume, complexity, and diversity of data currently being generated by scientific experiments and simulations often causes scientists to waste productive time. Scientific Data Management: Challenges, Technology, and Deployment describes cutting-edge technologies and solutions for managing and analyzing vast amounts of data, helping scientists focus on their scientific goals. The book begins with coverage of efficient storage systems, discussing how to write and read large volumes of data without slowing the simulation, analysis, or visualization processes. It then focuses on the efficient data movement and management of storage spaces and explores emerging database systems for scientific data. The book also addresses how to best organize data for analysis purposes, how to effectively conduct searches over large datasets, how to successfully automate multistep scientific process workflows, and how to automatically collect metadata and lineage information. This book provides a comprehensive understanding of the latest techniques for managing data during scientific exploration processes, from data generation to data analysis. Enhanced by numerous detailed color images, it includes real-world examples of applications drawn from biology, ecology, geology, climatology, and more. Check out Dr. Shoshani discuss the book during an interview with International Science Grid This Week (iSGTW): http://www.isgtw.org/?pid=1002259