Название: Maximum Availability Architecture (MAA) with Oracle GoldenGate MicroServices in HUB Architecture: Learn how to use Oracle GoldenGate to improve the availability, reliability, and scalability of your mission-critical systems
Автор: Luсiа Нustаtуоvа
Издательство: BPB Publications
Год: 2024
Страниц: 1273
Язык: английский
Формат: pdf, epub
Размер: 48.4 MB

A step-by-step guide for designing, implementing, and managing Oracle GoldenGate with HUB Architecture. Oracle GoldenGate is a software product that allows you to replicate data from one database to another. If you are interested in using Oracle GoldenGate Microservices (OGG MA) in HUB configuration for database upgrade, migration, and data replication, then this book is a valuable resource for you. This book provides step by step instructions, explanation about the whole architecture design for Oracle GoldenGate Microservices in HUB configuration including HA (High Availability) and DR (Disaster Recovery). This new technology is explained in the real project’s examples for the database upgrade/migration, data replication using OGG MA in HUB configuration, using REST API, command line solutions or web interface. Everything is explained from the beginning of the architecture design until full installation and administration. Book contains also real example of the code, how to handle different activities via REST API. Via Cloud Control will be installed OGG plugin to monitor all components. Architecture designed is proven at the end of the book, where is explained via example/execution that solution works as designed in the DR and HA situation.

Название: Amazon Redshift: The Definitive Guide: Jump-Start Analytics Using Cloud Data Warehousing
Автор: Rаjеsh Frаnсis, Rаjiv Guрtа, Мilind Оkе
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 456
Язык: английский
Формат: epub (true)
Размер: 24.1 MB

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. The book starts by laying the foundations of modern data strategy, explaining the fundamental concepts of data warehouse and architecture of Amazon Redshift. From there, the authors dive deep into key features of the service with relevant examples for data modeling, loading and transforming data including streaming ingestion, performance optimization, scaling, and security best practices. You will also find in-depth coverage of integration with other AWS services like Amazon SageMaker, Amazon Aurora ensuring you can leverage the broader AWS ecosystem to build robust and scalable data applications.

Название: Learning Snowflake SQL and Scripting: Generate, Retrieve, and Automate Snowflake Data
Автор: Аlаn Веаuliеu
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 762
Язык: английский
Формат: pdf, epub (true)
Размер: 11.2 MB

To help you on the path to becoming a Snowflake pro, this concise yet comprehensive guide reviews fundamentals and best practices for Snowflake's SQL and Scripting languages. Developers and data professionals will learn how to generate, modify, and query data in the Snowflake relational database management system as well as how to apply analytic functions for reporting. Author Alan Beaulieu also shows you how to create scripts, stored functions, and stored procedures to return data sets using Snowflake Scripting. This book is ideal whether you're new to databases and need to run queries or reports against a Snowflake database, or transitioning from databases such as Oracle, SQL Server, or MySQL to cloud-based platforms. What Is SQL Scripting? If you have programmed with a procedural language such as Java, C#, or Go, you are familiar with such programming constructs as looping, if-then-else, and exception handling. SQL, being a nonprocedural language, has none of these constructs. To bridge this gap, most database platforms provide both a nonprocedural SQL implementation along with a procedural language that includes both the SQL data statements such as select and insert along with all of the usual procedural programming constructs.

Название: Fuzzy Data Matching with SQL: Enhancing Data Quality and Query Performance
Автор: Jim Lehmer
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 425
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

If you were handed two different but related sets of data, what tools would you use to find the matches? What if all you had was SQL SELECT access to a database? In this practical book, author Jim Lehmer provides best practices, techniques, and tricks to help you import, clean, match, score, and think about heterogeneous data using SQL. DBAs, programmers, business analysts, and data scientists will learn how to identify and remove duplicates, parse strings, extract data from XML and JSON, generate SQL using SQL, regularize data and prepare datasets, and apply data quality and ETL approaches for finding the similarities and differences between various expressions of the same data. Full of real-world techniques, the examples in the book contain working code.

Название: Data Analytics and Digital Transformation
Автор: Erik Beulen, Marla A. Dans
Издательство: Routledge
Год: 2024
Страниц: 257
Язык: английский
Формат: pdf (true), djvu
Размер: 10.1 MB

Understanding the significance of data analytics is paramount for digital transformation but in many organizations they are separate units without fully aligned goals. As organizations are applying digital transformations to be adaptive and agile in a competitive environment, data analytics can play a critical role in their success. This book explores the crossroads between them and how to leverage their connection for improved business outcomes. The need to collaborate and share data is becoming an integral part of digital transformation. This not only creates new opportunities but also requires well-considered and continuously assessed decision-making as competitiveness is at stake. This book details approaches, concepts, and frameworks, as well as actionable insights and good practices, including combined data management and agile concepts. Volumes of data are growing at an unprecedented speed, driven by the Internet of Things (IoT) and unstructured data (e.g. social media content), as well as additional data generated by transforming into digital organizations. This feeds back into data analytics as well as Data Science, requiring even more mature data management and governance to achieve enriched insights. In addition, the need to collaborate and share data is becoming an integral part of digital transformations. This not only creates new opportunities but also requires well-considered and continuously assessed decision-making as competitiveness is at stake. This book details approaches, concepts, and frameworks, as well as actionable insights and good practices, including combined data management and agile concepts. In addition, a deep dive into privacy and ethics will be included.

Название: Practical Implementation of a Data Lake: Translating Customer Expectations into Tangible Technical Goals
Автор: Nayanjyoti Paul
Издательство: Apress
Год: 2023
Страниц: 219
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

This book explains how to implement a data lake strategy, covering the technical and business challenges architects commonly face. It also illustrates how and why client requirements should drive architectural decisions. Drawing upon a specific case from his own experience, author Nayanjyoti Paul begins with the consideration from which all subsequent decisions should flow: what does your customer need? He also describes the importance of identifying key stakeholders and the key points to focus on when starting a new project. Next, he takes you through the business and technical requirement-gathering process, and how to translate customer expectations into tangible technical goals. From there, you’ll gain insight into the security model that will allow you to establish security and legal guardrails, as well as different aspects of security from the end user’s perspective. You’ll learn which organizational roles need to be onboarded into the data lake, their responsibilities, the services they need access to, and how the hierarchy of escalations should work. Subsequent chapters explore how to divide your data lakes into zones, organize data for security and access, manage data sensitivity, and techniques used for data obfuscation. Audit and logging capabilities in the data lake are also covered before a deep dive into designing data lakes to handle multiple kinds and file formats and access patterns. For Data Scientists and Architects, Machine Learning Engineers, and Software Engineers.

Название: Big Data Analytics for Human-Computer Interactions: A New Era of Computation
Автор: Kuldeep Singh Kaswan, Anupam Baliyan, Jagjit Singh Dhatterwal
Издательство: Bentham Books
Серия: IoT and Big Data Analytics (Volume 3)
Год: 2023
Страниц: 392
Язык: английский
Формат: pdf (true), epub
Размер: 25.8 MB

Big Data is playing a vital role in HCI projects across a range of industries: healthcare, cybersecurity, forensics, education, business organizations, and scientific research. Big data analytics requires advanced tools and techniques to store, process and analyze the huge volume of data. Working on HCI projects requires specific skill sets to implement IT solutions. Big Data Analytics is a significant challenge in developing highly scalable data and data integration algorithms. New algorithms, methods, systems, and applications in Big Data Analytics are potential discoveries that will effectively identify valuable and hidden information in Big Data. This chapter discusses big data, and its history; Big Data drives the world's modern organizations. There is a need to convert Big Data into Business Intelligence that enterprises can readily deploy. Better data leads to better decision-making and improved strategies for organizations. Big Data Analytics for Human-Computer Interactions: A New Era of Computation is a comprehensive guide that discusses the evolution of Big Data in Human Computer Interaction from promise to reality. This book provides an introduction to Big Data and HCI, followed by an overview of the state-of-the-art algorithms for processing big data, Subsequent chapters also explain the characteristics, applications, opportunities and challenges of big data systems, by describing theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in designing HIC systems.

Название: Learn Data Mining Through Excel: A Step-by-Step Approach for Understanding Machine Learning Methods, 2nd Edition
Автор: Hong Zhou
Издательство: Apress
Год: 2023
Страниц: 289
Язык: английский
Формат: pdf (true), epub (true)
Размер: 31.9 MB

Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Most software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help, and this book will show you exactly how. This updated edition demonstrates how to work with data in a transparent manner using Excel. When you open an Excel file, data is visible immediately and you can work with it directly. You’ll see how to examine intermediate results even as you are still conducting your mining task, offering a deeper understanding of how data is manipulated, and results are obtained. These are critical aspects of the model construction process that are often hidden in software tools and programming language packages. Anyone who is interested in learning data mining or Machine Learning, especially data science visual learners and people skilled in Excel who would like to explore Data Science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended.

Название: Data Smart: Using Data Science to Transform Information into Insight, 2nd Edition
Автор: Jordan Goldmeier
Издательство: Wiley
Год: 2024
Страниц: 445
Язык: английский
Формат: pdf (true)
Размер: 33.6 MB

A straightforward and engaging approach to Data Science that skips the jargon and focuses on the essentials. In the newly revised second edition of Data Smart: Using Data Science to Transform Information into Insight, accomplished data scientist and speaker Jordan Goldmeier delivers an approachable and conversational approach to data science using Microsoft Excel’s easily understood features. The author also walks readers through the fundamentals of statistics, machine learning and powerful Artificial Intelligence (AI) concepts, focusing on how to learn by doing. Data Science is the transformation of data using mathematics and statistics into valuable insights, decisions, and products. At the end of this book, I’ll show you how to implement what we’ve built in Excel in R. In fact, this follows my own path in building data science tools for companies. First, I would lay out my ideas in Excel. Use the spreadsheet as a way to validate my ideas and make sure I understand exactly what the algorithms do. Then, usually, when I’m ready, I move it to R or Python.

Название: Beginning Power BI for Business Users: Learning to Turn Data into Insights
Автор: Paul D. Fuller
Издательство: Wiley
Год: 2024
Страниц: 288
Язык: английский
Формат: epub (true)
Размер: 39.5 MB

Discover the utility of your organization's data with Microsoft Power BI. In Beginning Power BI for Business Users: Learning to Turn Data into Insights, accomplished data professional and business intelligence expert Paul Fuller delivers an intuitive and accessible handbook for professionals seeking to use Microsoft's Power BI to access, analyze, understand, report, and act on the data available to their organizations. In the book, you'll discover Power BI's robust feature set, learn to ingest and model data, visualize and report on that data, and even use the DAX scripting language to unlock still more utility from Microsoft's popular program. Beginning with general principles geared to readers with no or little experience with reporting or data analytics tools, the author walks you through how to manipulate common, publicly available data sources—including Excel files and relational databases. As a data analytics engineer, I've loved using Power BI since it was introduced many years ago. But I'm a tech nerd. And many of the experts in Power BI are also geeks like me. But here's the thing—Power BI is meant to be a tool for business users and data analysts. It's intended to be simple enough to get started and see amazing things quickly but sophisticated enough that the information technology (IT) folks can use it as well.