Download or read book Rise of the Data Lakehouse written by Bill Inmon and published by . This book was released on 2023-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The data lakehouse is the next generation of the data warehouse and data lake, designed to meet today's complex and ever-changing analytics, machine learning, and data science requirements. Learn about the features and architecture of the data lakehouse, along with its powerful analytical infrastructure. Appreciate how the universal common connector blends structured, textual, analog, and IoT data. Maintain the lakehouse for future generations through Data Lakehouse Housekeeping and Data Future-proofing. Incorporate data catalogs, data lineage tools, and open source software into your architecture to ensure your data scientists, analysts, and end users live happily ever after. Deep dive into one specific implementation of a data lakehouse: the Databricks Lakehouse Platform.

Download or read book Building the Data Lakehouse written by Bill Inmon and published by Technics Publications. This book was released on 2021-10 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: The data lakehouse is the next generation of the data warehouse and data lake, designed to meet today's complex and ever-changing analytics, machine learning, and data science requirements. Learn about the features and architecture of the data lakehouse, along with its powerful analytical infrastructure. Appreciate how the universal common connector blends structured, textual, analog, and IoT data. Maintain the lakehouse for future generations through Data Lakehouse Housekeeping and Data Future-proofing. Know how to incorporate the lakehouse into an existing data governance strategy. Incorporate data catalogs, data lineage tools, and open source software into your architecture to ensure your data scientists, analysts, and end users live happily ever after.

Download or read book Rise of the Data Cloud written by Frank Slootman and published by AuthorHouse. This book was released on 2020-12-18 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rise of the Data Cloud is ushering in a new era of computing. The world’s digital data is mass migrating to the cloud, where it can be more effectively integrated, managed, and mobilized. The data cloud eliminates data siloes and enables data sharing with business partners, capitalizing on data network effects. It democratizes data analytics, making the most sophisticated data science tools accessible to organizations of all sizes. Data exchanges enable businesses to discover, explore, and easily purchase or sell data—opening up new revenue streams. Business leaders have long dreamed of data driving their organizations. Now, thanks to the Data Cloud, nothing stands in their way.

Download or read book Data Lakehouse in Action written by Pradeep Menon and published by Packt Publishing Ltd. This book was released on 2022-03-17 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Propose a new scalable data architecture paradigm, Data Lakehouse, that addresses the limitations of current data architecture patterns Key FeaturesUnderstand how data is ingested, stored, served, governed, and secured for enabling data analyticsExplore a practical way to implement Data Lakehouse using cloud computing platforms like AzureCombine multiple architectural patterns based on an organization's needs and maturity levelBook Description The Data Lakehouse architecture is a new paradigm that enables large-scale analytics. This book will guide you in developing data architecture in the right way to ensure your organization's success. The first part of the book discusses the different data architectural patterns used in the past and the need for a new architectural paradigm, as well as the drivers that have caused this change. It covers the principles that govern the target architecture, the components that form the Data Lakehouse architecture, and the rationale and need for those components. The second part deep dives into the different layers of Data Lakehouse. It covers various scenarios and components for data ingestion, storage, data processing, data serving, analytics, governance, and data security. The book's third part focuses on the practical implementation of the Data Lakehouse architecture in a cloud computing platform. It focuses on various ways to combine the Data Lakehouse pattern to realize macro-patterns, such as Data Mesh and Data Hub-Spoke, based on the organization's needs and maturity level. The frameworks introduced will be practical and organizations can readily benefit from their application. By the end of this book, you'll clearly understand how to implement the Data Lakehouse architecture pattern in a scalable, agile, and cost-effective manner. What you will learnUnderstand the evolution of the Data Architecture patterns for analyticsBecome well versed in the Data Lakehouse pattern and how it enables data analyticsFocus on methods to ingest, process, store, and govern data in a Data Lakehouse architectureLearn techniques to serve data and perform analytics in a Data Lakehouse architectureCover methods to secure the data in a Data Lakehouse architectureImplement Data Lakehouse in a cloud computing platform such as AzureCombine Data Lakehouse in a macro-architecture pattern such as Data MeshWho this book is for This book is for data architects, big data engineers, data strategists and practitioners, data stewards, and cloud computing practitioners looking to become well-versed with modern data architecture patterns to enable large-scale analytics. Basic knowledge of data architecture and familiarity with data warehousing concepts are required.

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.

Download or read book Data Quality Fundamentals written by Barr Moses and published by "O'Reilly Media, Inc.". This book was released on 2022-09-01 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do your product dashboards look funky? Are your quarterly reports stale? Is the data set you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to these questions, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck, from the data observability company Monte Carlo, explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies. Build more trustworthy and reliable data pipelines Write scripts to make data checks and identify broken pipelines with data observability Learn how to set and maintain data SLAs, SLIs, and SLOs Develop and lead data quality initiatives at your company Learn how to treat data services and systems with the diligence of production software Automate data lineage graphs across your data ecosystem Build anomaly detectors for your critical data assets

Download or read book Data Lake for Enterprises written by Tomcy John and published by Packt Publishing Ltd. This book was released on 2017-05-31 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to implementing your enterprise data lake using Lambda Architecture as the base About This Book Build a full-fledged data lake for your organization with popular big data technologies using the Lambda architecture as the base Delve into the big data technologies required to meet modern day business strategies A highly practical guide to implementing enterprise data lakes with lots of examples and real-world use-cases Who This Book Is For Java developers and architects who would like to implement a data lake for their enterprise will find this book useful. If you want to get hands-on experience with the Lambda Architecture and big data technologies by implementing a practical solution using these technologies, this book will also help you. What You Will Learn Build an enterprise-level data lake using the relevant big data technologies Understand the core of the Lambda architecture and how to apply it in an enterprise Learn the technical details around Sqoop and its functionalities Integrate Kafka with Hadoop components to acquire enterprise data Use flume with streaming technologies for stream-based processing Understand stream- based processing with reference to Apache Spark Streaming Incorporate Hadoop components and know the advantages they provide for enterprise data lakes Build fast, streaming, and high-performance applications using ElasticSearch Make your data ingestion process consistent across various data formats with configurability Process your data to derive intelligence using machine learning algorithms In Detail The term "Data Lake" has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together. This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient. By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake. Style and approach The book takes a pragmatic approach, showing ways to leverage big data technologies and lambda architecture to build an enterprise-level data lake.

Download or read book The Cloud Data Lake written by Rukmani Gopalan and published by "O'Reilly Media, Inc.". This book was released on 2022-12-12 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: More organizations than ever understand the importance of data lake architectures for deriving value from their data. Building a robust, scalable, and performant data lake remains a complex proposition, however, with a buffet of tools and options that need to work together to provide a seamless end-to-end pipeline from data to insights. This book provides a concise yet comprehensive overview on the setup, management, and governance of a cloud data lake. Author Rukmani Gopalan, a product management leader and data enthusiast, guides data architects and engineers through the major aspects of working with a cloud data lake, from design considerations and best practices to data format optimizations, performance optimization, cost management, and governance. Learn the benefits of a cloud-based big data strategy for your organization Get guidance and best practices for designing performant and scalable data lakes Examine architecture and design choices, and data governance principles and strategies Build a data strategy that scales as your organizational and business needs increase Implement a scalable data lake in the cloud Use cloud-based advanced analytics to gain more value from your data

Download or read book The Data Lakehouse written by Bill Inmon and published by . This book was released on 2023-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The data lakehouse is the next generation of the data warehouse and data lake, designed to meet today's complex and ever-changing modern information systems. This book shows you how to construct your data lakehouse as the foundation for your artificial intelligence (AI), machine learning (ML), and data mesh initiatives. Know the pitfalls and techniques for maximizing business value of your data lakehouse. In addition, be able to explain the core characteristics and critical success factors of a data lakehouse. By reviewing entry errors, key incompatibility, and ensuring good documentation, we can improve the data quality and believability of your lakehouse. Evaluate criteria for data quality, including accuracy, completeness, reliability, relevance, and timeliness. Understand the different types of storage for the lakehouse, including the under-utilized yet extremely valuable bulk storage. There are three data types in the data lakehouse (structured, textual, and analog/ IoT), and for each, learn how to build a robust foundation for artificial intelligence (AI), machine learning (ML), and data mesh. Leverage data models for structured data, ontologies and taxonomies for textual data, and distillation algorithms for analog/IoT data. Learn how to abstract these data types to accommodate future requirements and simplify data lineage. Apply Extract, Transform, and Load (ETL) to create a structure that returns the answers to business problems. The end result is a data lakehouse that meets our needs. Speaking of human needs, learn Maslow's Hierarchy of Data Lakehouse Needs. Next explore data integration geared for Al, ML, and data mesh. Then deep dive with us into all of the varieties of analytics within the lakehouse, including structured, textual, and analog analytics. Witness how descriptive data, data catalog, and metadata can increase the value of the lakehouse. We conclude with a detailed evolution of data architecture, from magnetic tape to the data lakehouse as a bedrock foundation for AI, ML, and data mesh.

Download or read book Introduction to Information Systems written by R. Kelly Rainer (Jr.) and published by John Wiley & Sons. This book was released on 2023-10-23 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: As digital transformation becomes increasingly central to effective corporate strategy, today's students must learn how information systems provide the foundation for modern business enterprises. Known for its rich Canadian content and focus on active learning, Introduction to Information Systems, Sixth Canadian Edition shows students how they can use IS to help their current or future employers increase profitability, improve customer service, manage daily operations, and drive impact in their markets. This course demonstrates that IT is the backbone of any business, whether a student is majoring in accounting, finance, marketing, human resources, production/operations management, or MIS. In short, students will learn how information systems provide the foundation for all modern organizations, whether they are public sector, private sector, for-profit, or not-for-profit.

Download or read book Big Data on Kubernetes written by Neylson Crepalde and published by Packt Publishing Ltd. This book was released on 2024-07-19 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain hands-on experience in building efficient and scalable big data architecture on Kubernetes, utilizing leading technologies such as Spark, Airflow, Kafka, and Trino Key Features Leverage Kubernetes in a cloud environment to integrate seamlessly with a variety of tools Explore best practices for optimizing the performance of big data pipelines Build end-to-end data pipelines and discover real-world use cases using popular tools like Spark, Airflow, and Kafka Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn today's data-driven world, organizations across different sectors need scalable and efficient solutions for processing large volumes of data. Kubernetes offers an open-source and cost-effective platform for deploying and managing big data tools and workloads, ensuring optimal resource utilization and minimizing operational overhead. If you want to master the art of building and deploying big data solutions using Kubernetes, then this book is for you. Written by an experienced data specialist, Big Data on Kubernetes takes you through the entire process of developing scalable and resilient data pipelines, with a focus on practical implementation. Starting with the basics, you’ll progress toward learning how to install Docker and run your first containerized applications. You’ll then explore Kubernetes architecture and understand its core components. This knowledge will pave the way for exploring a variety of essential tools for big data processing such as Apache Spark and Apache Airflow. You’ll also learn how to install and configure these tools on Kubernetes clusters. Throughout the book, you’ll gain hands-on experience building a complete big data stack on Kubernetes. By the end of this Kubernetes book, you’ll be equipped with the skills and knowledge you need to tackle real-world big data challenges with confidence.What you will learn Install and use Docker to run containers and build concise images Gain a deep understanding of Kubernetes architecture and its components Deploy and manage Kubernetes clusters on different cloud platforms Implement and manage data pipelines using Apache Spark and Apache Airflow Deploy and configure Apache Kafka for real-time data ingestion and processing Build and orchestrate a complete big data pipeline using open-source tools Deploy Generative AI applications on a Kubernetes-based architecture Who this book is for If you’re a data engineer, BI analyst, data team leader, data architect, or tech manager with a basic understanding of big data technologies, then this big data book is for you. Familiarity with the basics of Python programming, SQL queries, and YAML is required to understand the topics discussed in this book.

Download or read book Modern Big Data Architectures written by Dominik Ryzko and published by John Wiley & Sons. This book was released on 2020-03-31 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.

Download or read book Data Mesh written by Pradeep Menon and published by BPB Publications. This book was released on 2024-05-16 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mesh: The future of data architecture! KEY FEATURES ● Decentralize data with domain-oriented design. ● Enhance scalability and data autonomy. ● Implement robust governance across domains. DESCRIPTION "Data Mesh: Principles, patterns, architecture, and strategies for data-driven decision making" introduces Data Mesh which is a macro data architecture pattern designed to harmonize governance with flexibility. This book guides readers through the nuances of Data Mesh topologies, explaining how they can be tailored to meet specific organizational needs while balancing central control with domain-specific autonomy. The book delves into the Data Mesh governance framework, which provides a structured approach to manage and control decentralized data assets effectively. It emphasizes the importance of a well-implemented governance structure that ensures data quality, compliance, and access control across various domains. Additionally, the book outlines robust data cataloging and sharing strategies, enabling organizations to improve data discoverability, usage, and interoperability between cross-functional teams. Securing Data Mesh architectures is another critical focus. The text explores comprehensive security strategies that protect data across different layers of the architecture, ensuring data integrity and protecting against breaches. By implementing the strategies discussed, data professionals will strengthen their ability to safeguard sensitive information in a distributed environment, making this book a vital resource for anyone involved in data management, security, or governance. WHAT YOU WILL LEARN ● Understand the evolution and need for Data Mesh architectures. ● Learn the core principles and design for Data Mesh implementations. ● Identify and apply Data Mesh architectural patterns and components. ● Implement effective Data Mesh governance frameworks. ● Develop and execute a strategic data cataloging plan. ● Create comprehensive data-sharing strategies and security strategies within Data Mesh. WHO THIS BOOK IS FOR This book is ideal for data professionals, including chief data officers, chief analytics officers, chief information officers, enterprise data architects, data stewards, and data governance and compliance professionals. TABLE OF CONTENTS 1. Establishing the Data Mesh Context 2. Evolution of Data Architectures 3. Principles of Data Mesh Architecture 4. The Patterns of Data Mesh Architecture 5. Data Governance in a Data Mesh 6. Data Cataloging in a Data Mesh 7. Data Sharing in a Data Mesh 8. Data Security in a Data Mesh 9. Data Mesh in Practice Appendix: Key terms

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.

Download or read book Introduction to Information Systems written by R. Kelly Rainer and published by John Wiley & Sons. This book was released on 2023-09-20 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Information Systems, 10th Edition teaches undergraduate business majors how to use information technology to master their current or future jobs. Students will see how global businesses use technology and information systems to increase their profitability, gain market share, develop and improve their customer relations, and manage daily operations. This course demonstrates that IT is the backbone of any business, whether a student is majoring in accounting, finance, marketing, human resources, production/operations management, or MIS. In short, students will learn how information systems provide the foundation for all modern organizations, whether they are public sector, private sector, for-profit, or not-for-profit.

Download or read book Jumpstart Snowflake written by Dmitry Anoshin and published by Apress. This book was released on 2019-12-20 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud. With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use. Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses. What You Will Learn Know the key functionalities of Snowflake Set up security and access with cluster Bulk load data into Snowflake using the COPY command Migrate from a legacy data warehouse to Snowflake integrate the Snowflake data platform with modern business intelligence (BI) and data integration tools Who This Book Is For Those working with data warehouse and business intelligence (BI) technologies, and existing and potential Snowflake users

Download or read book Mastering the Modern Data Stack written by Nick Jewell, PhD and published by TinyTechMedia LLC. This book was released on 2023-09-28 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of digital transformation, becoming overwhelmed by the sheer volume of potential data management, analytics, and AI solutions is common. Then it's all too easy to become distracted by glossy vendor marketing, and then chase the latest shiny tool, rather than focusing on building resilient, valuable platforms that will outperform the competition. This book aims to fix a glaring gap for data professionals: a comprehensive guide to the full Modern Data Stack that's rooted in real-world capabilities, not vendor hype. It is full of hard-earned advice on how to get maximum value from your investments through tangible insights, actionable strategies, and proven best practices. It comprehensively explains how the Modern Data Stack is truly utilized by today's data-driven companies. Mastering the Modern Data Stack: An Executive Guide to Unified Business Analytics is crafted for a diverse audience. It's for business and technology leaders who understand the importance and potential value of data, analytics, and AI—but don’t quite see how it all fits together in the big picture. It's for enterprise architects and technology professionals looking for a primer on the data analytics domain, including definitions of essential components and their usage patterns. It's also for individuals early in their data analytics careers who wish to have a practical and jargon-free understanding of how all the gears and pulleys move behind the scenes in a Modern Data Stack to turn data into actual business value. Whether you're starting your data journey with modest resources, or implementing digital transformation in the cloud, you'll find that this isn't just another textbook on data tools or a mere overview of outdated systems. It's a powerful guide to efficient, modern data management and analytics, with a firm focus on emerging technologies such as data science, machine learning, and AI. If you want to gain a competitive advantage in today’s fast-paced digital world, this TinyTechGuide™ is for you. Remember, it’s not the tech that’s tiny, just the book!™