Implementing A Modern Data Catalog To Power Data Intelligence
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Implementing A Modern Data Catalog To Power Data Intelligence
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Author : Fadi Maali
language : en
Publisher:
Release Date : 2022
Implementing A Modern Data Catalog To Power Data Intelligence written by Fadi Maali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Big data categories.
Are you looking to use data as a strategic asset in your organization, so that more people can make better, data-driven decisions and accelerate time to value? This report explains how. Whether you're working on self-service analytics, data governance, or cloud data migration, authors Fadi Maali, an experienced data engineer and the lead editor of the DCAT Specification, and Jason Lim, director of product and cloud marketing at Alation, show you why a data catalog is the starting point and center of all of it. Modern data catalogs are collections of metadata describing data assets and their usage. They provide relevant functionality to support metadata management, enrichment, and search. Not only do these catalogs help you find relevant data, they also guide you through the data's proper use. This report shows you how a data catalog can help you easily find and then use the data you need.
Building Modern Data Applications Using Databricks Lakehouse
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Author : Will Girten
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-10-21
Building Modern Data Applications Using Databricks Lakehouse written by Will Girten and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-21 with categories.
Develop, optimize, and monitor data pipelines on Databricks
Amazon Redshift The Definitive Guide
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Author : Rajesh Francis
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-10-03
Amazon Redshift The Definitive Guide written by Rajesh Francis and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-03 with Computers categories.
Amazon Redshift powers analytic cloud data warehouses worldwide, from startups to some of the largest enterprise data warehouses available today. This practical guide thoroughly examines this managed service and demonstrates how you can use it to extract value from your data immediately, rather than go through the heavy lifting required to run a typical data warehouse. Analytic specialists Rajesh Francis, Rajiv Gupta, and Milind Oke detail Amazon Redshift's underlying mechanisms and options to help you explore out-of-the box automation. Whether you're a data engineer who wants to learn the art of the possible or a DBA looking to take advantage of machine learning-based auto-tuning, this book helps you get the most value from Amazon Redshift. By understanding Amazon Redshift features, you'll achieve excellent analytic performance at the best price, with the least effort. This book helps you: Build a cloud data strategy around Amazon Redshift as foundational data warehouse Get started with Amazon Redshift with simple-to-use data models and design best practices Understand how and when to use Redshift Serverless and Redshift provisioned clusters Take advantage of auto-tuning options inherent in Amazon Redshift and understand manual tuning options Transform your data platform for predictive analytics using Redshift ML and break silos using data sharing Learn best practices for security, monitoring, resilience, and disaster recovery Leverage Amazon Redshift integration with other AWS services to unlock additional value
Data Analysis With Microsoft Power Bi
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Author : Brian Larson
language : en
Publisher: McGraw Hill Professional
Release Date : 2020-01-03
Data Analysis With Microsoft Power Bi written by Brian Larson and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-03 with Computers categories.
Explore, create, and manage highly interactive data visualizations using Microsoft Power BI Extract meaningful business insights from your disparate enterprise data using the detailed information contained in this practical guide. Written by a recognized BI expert and bestselling author, Data Analysis with Microsoft Power BI teaches you the skills you need to interact with, author, and maintain robust visualizations and custom data models. Hands-on exercises based on real-life business scenarios clearly demonstrate each technique. Publishing your results to the Power BI Service (PowerBI.com) and Power BI Report Server are also fully covered. Inside, you will discover how to: •Understand Business Intelligence and self-service analytics •Explore the tools and features of Microsoft Power BI •Create and format effective data visualizations •Incorporate advanced interactivity and custom graphics •Build and populate accurate data models •Transform data using the Power BI Query Editor •Work with measures, calculated columns, and tabular models •Write powerful DAX language scripts •Share content on the PowerBI Service (PowerBI.com) •Store your visualizations on the Power BI Report Server
The Enterprise Big Data Lake
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Author : Alex Gorelik
language : en
Publisher: O'Reilly Media
Release Date : 2019-02-21
The Enterprise Big Data Lake written by Alex Gorelik and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-21 with Computers categories.
The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. You’ll learn what a data lake is, why enterprises need one, and how to build one successfully with the best practices in this book. Alex Gorelik, CTO and founder of Waterline Data, explains why old systems and processes can no longer support data needs in the enterprise. Then, in a collection of essays about data lake implementation, you’ll examine data lake initiatives, analytic projects, experiences, and best practices from data experts working in various industries. Get a succinct introduction to data warehousing, big data, and data science Learn various paths enterprises take to build a data lake Explore how to build a self-service model and best practices for providing analysts access to the data Use different methods for architecting your data lake Discover ways to implement a data lake from experts in different industries
Data Engineering With Apache Spark Delta Lake And Lakehouse
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Author : Manoj Kukreja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-22
Data Engineering With Apache Spark Delta Lake And Lakehouse written by Manoj Kukreja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Computers categories.
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.
Designing Data Intensive Applications
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Author : Martin Kleppmann
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-03-16
Designing Data Intensive Applications written by Martin Kleppmann and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-16 with Computers categories.
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
The Journey Continues From Data Lake To Data Driven Organization
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Author : Mandy Chessell
language : en
Publisher: IBM Redbooks
Release Date : 2018-02-19
The Journey Continues From Data Lake To Data Driven Organization written by Mandy Chessell and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-19 with Computers categories.
This IBM RedguideTM publication looks back on the key decisions that made the data lake successful and looks forward to the future. It proposes that the metadata management and governance approaches developed for the data lake can be adopted more broadly to increase the value that an organization gets from its data. Delivering this broader vision, however, requires a new generation of data catalogs and governance tools built on open standards that are adopted by a multi-vendor ecosystem of data platforms and tools. Work is already underway to define and deliver this capability, and there are multiple ways to engage. This guide covers the reasons why this new capability is critical for modern businesses and how you can get value from it.
The Enterprise Data Catalog Improve Data Discovery Ensure Data Governance And Enable Innovation
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Author : Ole Olesen-Bagneux
language : en
Publisher: O'Reilly Media
Release Date : 2023-05-30
The Enterprise Data Catalog Improve Data Discovery Ensure Data Governance And Enable Innovation written by Ole Olesen-Bagneux and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-30 with Computers categories.
How do you search for data? Combing the internet is simple. But do you search for data at work? It can be difficult and time-consuming. Sometimes it even seems impossible. This book introduces a practical solution: the data catalog. Data analysts, data scientists, and data engineers will learn how to create true data discovery in their organizations, making the catalog a key enabler for data-driven innovation and data governance. Author Ole Olesen-Bagneux, PhD, explains the benefits of implementing a data catalog. You'll learn how to organize the data for your catalog, search for the data you need, and manage the data once it's in the catalog. This book is written from a data management perspective but also from a library and information science perspective. Learn what a data catalog is and how it can help your organization search for data Organize data in a catalog, including its sources, where it belongs, and how to describe it with metadata Manage your data catalog, create access to data sources, and browse relational graph structures across systems and domains Learn how to search your data, including its sources, and how it travels and changes in data lineage Implement a data catalog in a way that exactly matches the strategic priorities of your organization
Google Earth Engine And Artificial Intelligence For Earth Observation
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Author : Vishakha Sood
language : en
Publisher: Elsevier
Release Date : 2025-03-31
Google Earth Engine And Artificial Intelligence For Earth Observation written by Vishakha Sood and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Technology & Engineering categories.
Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications explores a wide range of transformative data fusion techniques of Artificial Intelligence (AI) technologies applied to Google Earth Engine (GEE) techniques. It includes a wide range of scientific domains that can utilize remote sensing and geographic information systems (GIS) through detailed case studies. This book delves into the challenges of AI-driven tools and technologies for Earth observation data analysis, offering possible solutions and directly addressing current and upcoming needs within Earth observation. Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications is a useful reference for geospatial scientists, remote sensing experts, and environmental scientists utilizing remote sensing to apply the latest AI techniques to data obtained from GEE for their research and teaching. - Includes utilization of AI with GEE tools for a spectrum of scientific domains in remote sensing and geographic information systems (GIS) including natural hazard assessment, aquatic and hydrological applications, and forest cover - Highlights the challenges and possible solutions for AI-driven tools and technologies for Earth observation data analysis - Includes detailed case studies showing specific considerations and exceptions for applications of AI in GEE for Earth observation