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Modern Enterprise Data Pipelines
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Book Synopsis Modern Enterprise Data Pipelines by : Mike Bachman
Download or read book Modern Enterprise Data Pipelines written by Mike Bachman and published by . This book was released on 2021-06-25 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A Dell Technologies perspective on today's data landscape and the key ingredients for planning a modern, distributed data pipeline for your multicloud data-driven enterprise
Book Synopsis Architecting Modern Data Platforms by : Jan Kunigk
Download or read book Architecting Modern Data Platforms written by Jan Kunigk and published by "O'Reilly Media, Inc.". This book was released on 2018-12-05 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You’ll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into: Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability
Book Synopsis Predictive Analytics for the Modern Enterprise by : Nooruddin Abbas Ali
Download or read book Predictive Analytics for the Modern Enterprise written by Nooruddin Abbas Ali and published by "O'Reilly Media, Inc.". This book was released on 2024-05-20 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics on-premises or in the cloud. Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow
Book Synopsis Data Pipelines Pocket Reference by : James Densmore
Download or read book Data Pipelines Pocket Reference written by James Densmore and published by O'Reilly Media. This book was released on 2021-02-10 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Performance Dashboards by : Wayne W. Eckerson
Download or read book Performance Dashboards written by Wayne W. Eckerson and published by John Wiley & Sons. This book was released on 2005-10-27 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution.
Book Synopsis Data Pipelines with Apache Airflow by : Bas P. Harenslak
Download or read book Data Pipelines with Apache Airflow written by Bas P. Harenslak and published by Simon and Schuster. This book was released on 2021-04-27 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book teaches you how to build and maintain effective data pipelines. Youll explore the most common usage patterns, including aggregating multiple data sources, connecting to and from data lakes, and cloud deployment. --
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.
Book Synopsis The Modern Business Data Analyst by : Dominik Jung
Download or read book The Modern Business Data Analyst written by Dominik Jung and published by Springer Nature. This book was released on 2024 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book illustrates and explains the key concepts of business data analytics from scratch, tackling the day-to-day challenges of a business data analyst. It provides you with all the professional tools you need to predict online shop sales, to conduct A/B tests on marketing campaigns, to generate automated reports with PowerPoint, to extract datasets from Wikipedia, and to create interactive analytics Web apps. Alongside these practical projects, this book provides hands-on coding exercises, case studies, the essential programming tools and the CRISP-DM framework which you'll need to kickstart your career in business data analytics. The different chapters prioritize practical understanding over mathematical theory, using realistic business data and challenges of the Junglivet Whisky Company to intuitively grasp key concepts and ideas. Designed for beginners and intermediates, this book guides you from business data analytics fundamentals to advanced techniques, covering a large number of different techniques and best-practices which you can immediately exploit in your daily work. The book does not assume that you have an academic degree or any experience with business data analytics or data science. All you need is an open mind, willingness to puzzle and think mathematically, and the willingness to write some R code. This book is your all-in-one resource to become proficient in business data analytics with R, equipped with practical skills for the real world.
Download or read book Spring Data written by Mark Pollack and published by "O'Reilly Media, Inc.". This book was released on 2012-10-24 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring Data makes it relatively easy to build applications across a wide range of new data access technologies such as NoSQL and Hadoop. Through several sample projects, you’ll learn how Spring Data provides a consistent programming model that retains NoSQL-specific features and capabilities, and helps you develop Hadoop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow. You’ll also discover the features Spring Data adds to Spring’s existing JPA and JDBC support for writing RDBMS-based data access layers. Learn about Spring’s template helper classes to simplify the use of database-specific functionality Explore Spring Data’s repository abstraction and advanced query functionality Use Spring Data with Redis (key/value store), HBase (column-family), MongoDB (document database), and Neo4j (graph database) Discover the GemFire distributed data grid solution Export Spring Data JPA-managed entities to the Web as RESTful web services Simplify the development of HBase applications, using a lightweight object-mapping framework Build example big-data pipelines with Spring Batch and Spring Integration
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
Book Synopsis TRANSFORMING DATA PIPELINES WITH GENERATIVE AI AND DEEP LEARNING by : Arun Kumar Ramachandran Sumangala Devi
Download or read book TRANSFORMING DATA PIPELINES WITH GENERATIVE AI AND DEEP LEARNING written by Arun Kumar Ramachandran Sumangala Devi and published by BUDHA PUBLISHER. This book was released on with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: ....
Book Synopsis Data Engineering with Apache Spark, Delta Lake, and Lakehouse by : Manoj Kukreja
Download or read book Data Engineering with Apache Spark, Delta Lake, and Lakehouse written by Manoj Kukreja and published by Packt Publishing Ltd. This book was released on 2021-10-22 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the complexities of modern-day data engineering platforms and explore strategies to deal with them with the help of use case scenarios led by an industry expert in big data Key FeaturesBecome well-versed with the core concepts of Apache Spark and Delta Lake for building data platformsLearn how to ingest, process, and analyze data that can be later used for training machine learning modelsUnderstand how to operationalize data models in production using curated dataBook Description In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. You'll cover data lake design patterns and the different stages through which the data needs to flow in a typical data lake. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. Finally, you'll cover data lake deployment strategies that play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous way. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. What you will learnDiscover the challenges you may face in the data engineering worldAdd ACID transactions to Apache Spark using Delta LakeUnderstand effective design strategies to build enterprise-grade data lakesExplore architectural and design patterns for building efficient data ingestion pipelinesOrchestrate a data pipeline for preprocessing data using Apache Spark and Delta Lake APIsAutomate deployment and monitoring of data pipelines in productionGet to grips with securing, monitoring, and managing data pipelines models efficientlyWho this book is for This book is for aspiring data engineers and data analysts who are new to the world of data engineering and are looking for a practical guide to building scalable data platforms. If you already work with PySpark and want to use Delta Lake for data engineering, you'll find this book useful. Basic knowledge of Python, Spark, and SQL is expected.
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
Book Synopsis Designing Cloud Data Platforms by : Danil Zburivsky
Download or read book Designing Cloud Data Platforms written by Danil Zburivsky and published by Simon and Schuster. This book was released on 2021-04-20 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Centralized data warehouses, the long-time defacto standard for housing data for analytics, are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services. Designing Cloud Data Platforms is an hands-on guide to envisioning and designing a modern scalable data platform that takes full advantage of the flexibility of the cloud. As you read, you''ll learn the core components of a cloud data platform design, along with the role of key technologies like Spark and Kafka Streams. You''ll also explore setting up processes to manage cloud-based data, keep it secure, and using advanced analytic and BI tools to analyse it. about the technology Access to affordable, dependable, serverless cloud services has revolutionized the way organizations can approach data management, and companies both big and small are raring to migrate to the cloud. But without a properly designed data platform, data in the cloud can remain just as siloed and inaccessible as it is today for most organizations. Designing Cloud Data Platforms lays out the principles of a well-designed platform that uses the scalable resources of the public cloud to manage all of an organization''s data, and present it as useful business insights. about the book In Designing Cloud Data Platforms, you''ll learn how to integrate data from multiple sources into a single, cloud-based, modern data platform. Drawing on their real-world experiences designing cloud data platforms for dozens of organizations, cloud data experts Danil Zburivsky and Lynda Partner take you through a six-layer approach to creating cloud data platforms that maximizes flexibility and manageability and reduces costs. Starting with foundational principles, you''ll learn how to get data into your platform from different databases, files, and APIs, the essential practices for organizing and processing that raw data, and how to best take advantage of the services offered by major cloud vendors. As you progress past the basics you''ll take a deep dive into advanced topics to get the most out of your data platform, including real-time data management, machine learning analytics, schema management, and more. what''s inside The tools of different public cloud for implementing data platforms Best practices for managing structured and unstructured data sets Machine learning tools that can be used on top of the cloud Cost optimization techniques about the reader For data professionals familiar with the basics of cloud computing and distributed data processing systems like Hadoop and Spark. about the authors Danil Zburivsky has over 10 years experience designing and supporting large-scale data infrastructure for enterprises across the globe. Lynda Partner is the VP of Analytics-as-a-Service at Pythian, and has been on the business side of data for over 20 years.
Book Synopsis Future And Fintech, The: Abcdi And Beyond by : Jun Xu
Download or read book Future And Fintech, The: Abcdi And Beyond written by Jun Xu and published by World Scientific. This book was released on 2022-05-05 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Future and FinTech examines the fundamental financial technologies and its growing impact on the Banking, Financial Services and Insurance (BFSI) sectors. With global investment amounting to more than $100 billion in 2020, the proliferation of FinTech has underpinned the direction payments, loans, wealth management, insurance, and cryptocurrencies are heading.This book presents FinTech from an industrial perspective in the context of architecture and its basic building blocks, e.g., Artificial Intelligence (AI), Blockchain, Cloud, Big Data, Internet of Things (IoT), and its connections to real-life applications at work. It provides a detailed guidance on how FinTech digitalizes business operations, improves productivity and efficiency, and optimizes resource management with the help of some new concepts, such as AIOps, MLOps and DevSecOps. Readers will also discover how FinTech Innovations connect BFSI to the rest of the world with growing interests in Open Banking, Banking-as-a-Service (BaaS) and FinTech-as-a-Service (FaaS).To help readers understand how FinTech has unlocked numerous opportunities for tapping into the massive substantial group of customers, this book illustrates the massive changes already underway and provides insights into changes yet to come through practical examples and applications with illustrative figures and summary tables, making this book a handy quick reference for all things of FinTech.Related Link(s)
Download or read book DAMA-DMBOK written by Dama International and published by . This book was released on 2017 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
Book Synopsis Snowflake: The Definitive Guide by : Joyce Kay Avila
Download or read book Snowflake: The Definitive Guide written by Joyce Kay Avila and published by "O'Reilly Media, Inc.". This book was released on 2022-08-11 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Snowflake's ability to eliminate data silos and run workloads from a single platform creates opportunities to democratize data analytics, allowing users at all levels within an organization to make data-driven decisions. Whether you're an IT professional working in data warehousing or data science, a business analyst or technical manager, or an aspiring data professional wanting to get more hands-on experience with the Snowflake platform, this book is for you. You'll learn how Snowflake users can build modern integrated data applications and develop new revenue streams based on data. Using hands-on SQL examples, you'll also discover how the Snowflake Data Cloud helps you accelerate data science by avoiding replatforming or migrating data unnecessarily. You'll be able to: Efficiently capture, store, and process large amounts of data at an amazing speed Ingest and transform real-time data feeds in both structured and semistructured formats and deliver meaningful data insights within minutes Use Snowflake Time Travel and zero-copy cloning to produce a sensible data recovery strategy that balances system resilience with ongoing storage costs Securely share data and reduce or eliminate data integration costs by accessing ready-to-query datasets available in the Snowflake Marketplace
