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Books > Computing & IT > Applications of computing > Databases > Data warehousing

Instant Pentaho Data Integration Kitchen (Paperback): Sergio Ramazzina Instant Pentaho Data Integration Kitchen (Paperback)
Sergio Ramazzina
R775 Discovery Miles 7 750 Ships in 10 - 15 working days

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A practical guide with easy-to-follow recipes helping developers to quickly and effectively collect data from disparate sources such as databases, files, and applications, and turn the data into a unified format that is accessible and relevant to end users.Any IT professional working on PDI and is a valid support for either learning how to use the command line tools efficiently or for going deeper on some aspects of the command line tools to help you work better.

Logic and Relational Theory - Thoughts and Essays on Database Matters (Paperback): Chris Date Logic and Relational Theory - Thoughts and Essays on Database Matters (Paperback)
Chris Date
R1,078 R940 Discovery Miles 9 400 Save R138 (13%) Ships in 10 - 15 working days
Learning to Love Data Science (Paperback): Mike Barloe Learning to Love Data Science (Paperback)
Mike Barloe
R595 R486 Discovery Miles 4 860 Save R109 (18%) Ships in 12 - 19 working days

Until recently, many people thought big data was a passing fad. "Data science" was an enigmatic term. Today, big data is taken seriously, and data science is considered downright sexy. With this anthology of reports from award-winning journalist Mike Barlow, you'll appreciate how data science is fundamentally altering our world, for better and for worse. Barlow paints a picture of the emerging data space in broad strokes. From new techniques and tools to the use of data for social good, you'll find out how far data science reaches. With this anthology, you'll learn how: Analysts can now get results from their data queries in near real time Indie manufacturers are blurring the lines between hardware and software Companies try to balance their desire for rapid innovation with the need to tighten data security Advanced analytics and low-cost sensors are transforming equipment maintenance from a cost center to a profit center CIOs have gradually evolved from order takers to business innovators New analytics tools let businesses go beyond data analysis and straight to decision-making Mike Barlow is an award-winning journalist, author, and communications strategy consultant. Since launching his own firm, Cumulus Partners, he has represented major organizations in a number of industries.

Big Data Imperatives - Enterprise Big Data Warehouse, BI Implementations and Analytics (Paperback, 1st ed.): Soumendra Mohanty,... Big Data Imperatives - Enterprise Big Data Warehouse, BI Implementations and Analytics (Paperback, 1st ed.)
Soumendra Mohanty, Madhu Jagadeesh, Harsha Srivatsa
R2,223 Discovery Miles 22 230 Ships in 10 - 15 working days

Big Data Imperatives, focuses on resolving the key questions on every one's mind: Which data matters? Do you have enough data volume to justify the usage? How you want to process this amount of data? How long do you really need to keep it active for your analysis, marketing, and BI applications? Big data is emerging from the realm of one-off projects to mainstream business adoption; however the real value of big data is not in the overwhelming size of it, but more in its effective use. Your goal may be to obtain insight from voluminous data, with billions of loosely-structured bytes of data coming from different channels spread across different locations, which needs to be processed until the needle in the haystack is found.This book addresses the following big data characteristics: * Very large, distributed aggregations of loosely structured data -- often incomplete and inaccessible * Petabytes/Exabytes of data * Millions/billions of people providing/contributing to the context behind the data * Flat schema's with few complex interrelationships * Involves time-stamped events * Made up of incomplete data * Includes connections between data elements that must be probabilistically inferred Big data imperatives, explains 'what big data can do'. It can batch process millions and billions of records both unstructured and structured much faster and cheaper. Big data analytics provide a platform, to merge all analysis which enables data analysis to be more accurate, well-rounded, reliable and focused on a specific business capability. Big data imperatives, describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other.This book aims to bring the big data and analytics realms together with a greater focus on architectures that leverage the scale and power of big data and the ability to integrate and apply analytics principles to data which earlier was not accessible. This book, can also be used as a handbook for practitioners; helping them on methodology, technical architecture, analytics techniques and best practices. At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data. What you'll learn * Understanding the technology, implementation of big data platforms and their usage for analytics * Big data architectures * Big data design patterns * Implementation best practices Who this book is for This book is designed for IT professionals, data warehousing, business intelligence professionals, data analysis professionals, architects, developers and business users

The Semantic Web - ISWC 2010 - 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010,... The Semantic Web - ISWC 2010 - 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I (Paperback, 2011 ed.)
Peter F. Patel-Schneider, Yue Pan, Pascal Hitzler, Peter Mika, Lei Zhang, …
R3,037 Discovery Miles 30 370 Ships in 10 - 15 working days

The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.

Data Warehousing and Knowledge Discovery - 11th International Conference, DaWaK 2009 Linz, Austria, August 31-September 2, 2009... Data Warehousing and Knowledge Discovery - 11th International Conference, DaWaK 2009 Linz, Austria, August 31-September 2, 2009 Proceedings (Paperback, 2009 ed.)
Mukesh K Mohania, A. Min Tjoa
R1,580 Discovery Miles 15 800 Ships in 10 - 15 working days

Data warehousing and knowledge discovery are increasingly becoming mission-critical technologies for most organizations, both commercial and public, as it becomes incre- ingly important to derive important knowledge from both internal and external data sources. With the ever growing amount and complexity of the data and information available for decision making, the process of data integration, analysis, and knowledge discovery continues to meet new challenges, leading to a wealth of new and exciting research challenges within the area. Over the last decade, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has established itself as one of the most important international scientific events within data warehousing and knowledge discovery. DaWaK brings together a wide range of researchers and practitioners working on these topics. The DaWaK conference series thus serves as a leading forum for discu- ing novel research results and experiences within data warehousing and knowledge th discovery. This year's conference, the 11 International Conference on Data Wa- housing and Knowledge Discovery (DaWaK 2009), continued the tradition by d- seminating and discussing innovative models, methods, algorithms, and solutions to the challenges faced by data warehousing and knowledge discovery technologies.

The Kimball Group Reader - Relentlessly Practical Tools for Data Warehousing and Business Intelligence, 2e (Paperback, 2nd... The Kimball Group Reader - Relentlessly Practical Tools for Data Warehousing and Business Intelligence, 2e (Paperback, 2nd Revised edition)
R. Kimball
R1,275 Discovery Miles 12 750 Ships in 9 - 17 working days

The final edition of the incomparable data warehousing and business intelligence reference, updated and expanded The Kimball Group Reader, Remastered Collection is the essential reference for data warehouse and business intelligence design, packed with best practices, design tips, and valuable insight from industry pioneer Ralph Kimball and the Kimball Group. This Remastered Collection represents decades of expert advice and mentoring in data warehousing and business intelligence, and is the final work to be published by the Kimball Group. Organized for quick navigation and easy reference, this book contains nearly 20 years of experience on more than 300 topics, all fully up-to-date and expanded with 65 new articles. The discussion covers the complete data warehouse/business intelligence lifecycle, including project planning, requirements gathering, system architecture, dimensional modeling, ETL, and business intelligence analytics, with each group of articles prefaced by original commentaries explaining their role in the overall Kimball Group methodology. Data warehousing/business intelligence industry's current multi-billion dollar value is due in no small part to the contributions of Ralph Kimball and the Kimball Group. Their publications are the standards on which the industry is built, and nearly all data warehouse hardware and software vendors have adopted their methods in one form or another. This book is a compendium of Kimball Group expertise, and an essential reference for anyone in the field. * Learn data warehousing and business intelligence from the field's pioneers * Get up to date on best practices and essential design tips * Gain valuable knowledge on every stage of the project lifecycle * Dig into the Kimball Group methodology with hands-on guidance Ralph Kimball and the Kimball Group have continued to refine their methods and techniques based on thousands of hours of consulting and training. This Remastered Collection of The Kimball Group Reader represents their final body of knowledge, and is nothing less than a vital reference for anyone involved in the field.

Business unIntelligence - Insight & Innovation Beyond Analytics & Big Data (Paperback): Barry Devlin Business unIntelligence - Insight & Innovation Beyond Analytics & Big Data (Paperback)
Barry Devlin
R1,054 R916 Discovery Miles 9 160 Save R138 (13%) Ships in 10 - 15 working days

Business intelligence (BI) used to be so simple -- in theory anyway. Integrate and copy data from your transactional systems into a specialised relational database, apply BI reporting and query tools and add business users. Job done. No longer. Analytics, big data and an array of diverse technologies have changed everything. More importantly, business is insisting on ever more, ever faster from information and from IT in general. An emerging biz-tech ecosystem demands that business and IT work together. This book reflects the new reality that in todays socially complex and rapidly changing world, business decisions must be based on a combination of rational and intuitive thinking. Integrating cues from diverse information sources and tacit knowledge, decision makers create unique meaning to innovate heuristically at the speed of thought. This book provides a wealth of new models that business and IT can use together to design support systems for tomorrows successful organisations. Dr Barry Devlin, one of the earliest proponents of data warehousing, goes back to basics to explore how the modern trinity of information, process and people must be reinvented and restructured to deliver the value, insight and innovation required by modern businesses. From here, he develops a series of novel architectural models that provide a new foundation for holistic information use across the entire business. From discovery to analysis and from decision making to action taking, he defines a fully integrated, closed-loop business environment. Covering every aspect of business analytics, big data, collaborative working and more, this book takes over where BI ends to deliver the definitive framework for information use in the coming years.

Data Resource Understanding - Utilizing the Data Resource Data (Paperback): Michael Brackett Data Resource Understanding - Utilizing the Data Resource Data (Paperback)
Michael Brackett
R992 R853 Discovery Miles 8 530 Save R139 (14%) Ships in 10 - 15 working days
Data Modeling Made Simple with erwin DM (Paperback): Jeff Harris, Steve Hoberman Data Modeling Made Simple with erwin DM (Paperback)
Jeff Harris, Steve Hoberman
R2,036 R1,680 Discovery Miles 16 800 Save R356 (17%) Ships in 10 - 15 working days
Salesforce Data Architect Certification Guide - Comprehensive coverage of the Salesforce Data Architect exam content to help... Salesforce Data Architect Certification Guide - Comprehensive coverage of the Salesforce Data Architect exam content to help you pass on the first attempt (Paperback)
Aaron Allport
R1,146 Discovery Miles 11 460 Ships in 10 - 15 working days

Learn data architecture essentials and prepare for the Salesforce Certified Data Architect exam with the help of tips and mock test questions Key Features * Leverage data modelling, Salesforce database design, and techniques for effective data design * Learn master data management, Salesforce data management, and how to include considerations * Get to grips with large data volumes, performance tuning, and poor performance mitigation techniques Book Description The Salesforce Data Architect is a prerequisite exam for the Application Architect half of the Salesforce Certified Technical Architect credential. This book offers a complete, up-to-date coverage of the Salesforce Data Architect exam so you can take it with confidence. The book is written in a clear, succinct way with self-assessment and practice exam questions, covering all topics necessary to help you pass the exam with ease. You'll understand the theory around Salesforce data modeling, database design, master data management (MDM), Salesforce data management (SDM), and data governance. Additionally, performance considerations associated with large data volumes will be covered. You'll also get to grips with data migration and understand the supporting theory needed to achieve Salesforce Data Architect certification. By the end of this Salesforce book, you'll have covered everything you need to pass the Salesforce Data Architect certification exam and have a handy, on-the-job desktop reference guide to re-visit the concepts. What you will learn * Understand the topics relevant to passing the Data Architect exam * Explore specialist areas such as large data volumes * Test your knowledge with the help of exam-like questions * Pick up useful tips and tricks that can be referred to time and again * Understand the reasons underlying the way Salesforce data management works * Discover the techniques that are available for loading massive amounts of data Who This Book Is For This book is for both aspiring Salesforce data architects and those already familiar with Salesforce data architecture who want to pass the exam and have a reference guide to revisit the material as part of their day-to-day job. Working knowledge of the Salesforce platform is assumed, alongside a clear understanding of Salesforce architectural concepts.

Knowledge Management und Business Intelligence (German, Paperback, Softcover reprint of the original 1st ed. 2002): Uwe Hannig Knowledge Management und Business Intelligence (German, Paperback, Softcover reprint of the original 1st ed. 2002)
Uwe Hannig
R2,438 Discovery Miles 24 380 Ships in 10 - 15 working days

Wettbewerbsvorteile werden in Zukunft nur noch die Unternehmen erlangen, denen es gelingt, Informationen in Wissen zu verwandeln. Die zwei Welten Business Intelligence und Knowledge Management wachsen vor diesem Hintergrund zusammen. Der Herausgeber, Leiter des Instituts fur Managementinformationssysteme und des Instituts fur Knowledge Management, zeigt in diesem Buch die zunehmende Integration der beiden Bereiche. Das Buch bringt damit Transparenz in einen der groessten IT-Wachstumsmarkte. Mehrere Studien, etwa des Fraunhofer Instituts, beleuchten den relevanten Markt und geben wichtige Orientierungshilfen. Anhand einer Vielzahl von Beispielen wird gezeigt, welchen Nutzen der Einsatz hochentwickelter Analysewerkzeuge und die Entwicklung von Loesungen fur das Wissensmanagement heute bereits erbringen. Ebenfalls sehr hilfreich fur Praktiker ist die umfangreiche Anbieterliste. Einen raschen UEberblick uber die wichtigsten KM- und BI-Begriffe bietet ferner das integrierte Glossar.

Data Warehousing Strategie - Erfahrungen, Methoden, Visionen (German, Paperback, Softcover reprint of the original 1st ed.... Data Warehousing Strategie - Erfahrungen, Methoden, Visionen (German, Paperback, Softcover reprint of the original 1st ed. 2000)
Reinhard Jung, Robert Winter
R1,277 Discovery Miles 12 770 Ships in 10 - 15 working days

Data Warehousing ist seit einigen Jahren in vielen Branchen ein zentrales Thema. Die anfangliche Euphorie tauschte jedoch daruber hinweg, dass zur praktischen Umsetzung gesicherte Methoden und Vorgehensmodelle fehlten. Dieses Buch stellt einen Beitrag zur UEberwindung dieser Lucke zwischen Anspruch und Wirklichkeit dar. Es gibt im ersten Teil einen UEberblick uber aktuelle Ergebnisse im Bereich des Data Warehousing mit einem Fokus auf methodischen und betriebswirtschaftlichen Aspekten. Es finden sich u.a. Beitrage zur Wirtschaftlichkeitsanalyse, zur organisatorischen Einbettung des Data Warehousing, zum Datenqualitatsmanagement, zum integrierten Metadatenmanagement und zu datenschutzrechtlichen Aspekten sowie ein Beitrag zu moeglichen zukunftigen Entwicklungsrichtungen des Data Warehousing. Im zweiten Teil berichten Projektleiter umfangreicher Data Warehousing-Projekte uber Erfahrungen und Best Practices.

Data Warehouse Managementhandbuch - Konzepte, Software, Erfahrungen (German, Paperback, Softcover Reprint of the Original 1st... Data Warehouse Managementhandbuch - Konzepte, Software, Erfahrungen (German, Paperback, Softcover Reprint of the Original 1st 2001 ed.)
Reinhard Schutte, T Rotthowe, R Holten
R3,128 Discovery Miles 31 280 Ships in 10 - 15 working days

Problemloesungen fur das Top-Management: Das Buch stellt speziell fur Entscheidungstrager die Nutzungsmoeglichkeiten von Data-Warahouse-Konzepten vor. Neben den Grundlagen werden vor allem die Einsatzgebiete, verfugbare Loesungen und praktische Erfahrungen beschrieben. Das Management speziell aus Konsumguterindustrie und -handel erhalt so die Moeglichkeit, fur das eigene Unternehmen die optimale Entscheidung zu treffen.

Practical Data Science on Databricks - Scaling end-to-end machine learning on Databricks (Paperback): Debu Sinha Practical Data Science on Databricks - Scaling end-to-end machine learning on Databricks (Paperback)
Debu Sinha
R1,103 Discovery Miles 11 030 Ships in 10 - 15 working days

Develop the must-have skills required for any data scientist to get the best results from Azure Databricks. Key Features * Learn to develop and productionize ML pipelines using the Databricks Unified Analytics platform * See how to use AutoML, Feature Stores, and MLOps with Databricks * Get a complete understanding of data governance and model deployment Book Description In this book, you'll get to grips with Databricks, enabling you to power-up your organization's data science applications. We'll walk through applying the Databricks AI and ML stack to real-world use cases for natural language processing, computer vision, time series data, and more. We'll dive deep into the complete model development life cycle for data ingestion and analysis, and get familiar with the latest offerings of AutoML, Feature Store, and MLStudio, on the Databricks platform. You'll get hands-on experience implementing repeatable ML operations (MLOps) pipeline using MLFlow, track model training and key metrics, and explore real-time ML, anomaly detection, and streaming analytics with Delta lake and Spark Structured Streaming. Starting with an overview of Data Science use cases across different organizations and industries, you will then be introduced to feature stores, feature tables, and how to access them. You will see why AutoML is important and how to create a baseline model with AutoML within Databricks. Utilizing the ML Flow model registry to manage model versioning and transition to production will be covered, along with detecting and protecting against model drift in production environments. By the end of the book, you will know how to set up your Databricks ML development and deployment as a CI/CD pipeline. What you will learn * Perform natural language processing, computer vision, and more * Explore AutoML, Feature Store, and MLStudio on Databricks * Dive deep into the complete model development life cycle * Experience implementing repeatable MLOps pipelines using MLFlow * Track model training and key metrics * Explore real-time ML, anomaly detection, and streaming analytics * Learn how to handle model drift Who This Book Is For In this book we are going to specifically focus on the tools catering to the Data Scientist persona. Readers who want to learn how to successfully build and deploy end-end Data Science projects using the Databricks cloud agnostic unified analytics platform will benefit from this book, along with AI and Machine Learning practitioners.

Serverless Machine Learning with Amazon Redshift - Create, train, and deploy machine learning models using familiar SQL... Serverless Machine Learning with Amazon Redshift - Create, train, and deploy machine learning models using familiar SQL commands (Paperback)
Debabrata Panda, Phil Bates, Bhanu Pittampally, Sumeet Joshi
R1,212 Discovery Miles 12 120 Ships in 10 - 15 working days

Supercharge and deploy Amazon Redshift Serverless, train and deploy Machine learning Models using Amazon Redshift ML and run inference queries at scale. Key Features * Learn to build Multi-Class Classification Models * Create a model, validate a model and draw conclusion from K-means clustering * Learn to create a SageMaker endpoint and use that to create a Redshift ML Model for remote inference Book Description Amazon Redshift Serverless enables organizations to run PetaBytes scales Cloud data warehouses in minutes and in most cost effective way Developers, data analysts and BI analysts can deploy cloud data warehouses and use easy-to-use tools to train models and run predictions. Developers working with Amazon Redshift data warehouses will be able to put their SQL knowledge to work with this practical guide to train and deploy Machine Learning Models. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time. Complete with step-by-step explanations of essential concepts, practical examples and self-assessment questions, you will begin Deploying and Using Amazon Redshift Serverless and then dive into learning and deploying various types of Machine learning projects using familiar SQL Code. You will learn how to configure and deploy Amazon Redshift Serverless, understand the foundations of data analytics and types of data machine learning. Then you will deep dive into Redshift ML By the end of this book, you will be able to configure and deploy Amazon Redshift Serverless, train and deploy Machine learning Models using Amazon Redshift ML and run inference queries at scale. What you will learn * Learn how to implement an end-to-end serverless architecture for ingestion, analytics and machine learning using Redshift Serverless and Redshift ML * Learn how to create supervised and unsupervised models, and various techniques to influence your model * Learn how to run inference queries at scale in Redshift to solve a variety of business problems using models created with Redshift ML or natively in Amazon SageMaker * Learn how to optimize your Redshift data warehouse for extreme performance * Learn how to ensure you are using proper security guidelines with Redshift ML * Learn how to use model explainability in Amazon Redshift ML, to help understand how each attribute in your training data contributes to the predicted result. Who This Book Is For Data Scientists and Machine Learning developers who work with Amazon Redshift and want to explore it's machine learning capabilities will find this definitive guide helpful. Basic understanding of machine learning techniques and working knowledge of Amazon Redshift is needed to get the best from this book.

Monetare Integration - Bestandsaufnahme Und Weiterentwicklung Der Neueren Theorie (German, Paperback, 2001 ed.): Waltraud... Monetare Integration - Bestandsaufnahme Und Weiterentwicklung Der Neueren Theorie (German, Paperback, 2001 ed.)
Waltraud Schelkle
R1,479 Discovery Miles 14 790 Ships in 10 - 15 working days

Das anhaltende Interesse an der Theorie monetArer Integration ist einerseits dem europAischen EinigungsprozeA zu verdanken, andererseits der InstabilitAt des WeltwAhrungssystems seit dem Zusammenbruch der Bretton-Woods-Vereinbarung. Die vorherrschende Theorie des optimalen WAhrungsraumes hat sich jedoch angesichts neuerer Entwicklungen in der Theorie der Wirtschaftspolitik sowie in der Theorie des Wechselkurses als zu eng und methodisch fragwA1/4rdig erwiesen. Das Buch gibt einen umfassenden, auch fA1/4r AngehArige anderer sozialwissenschaftlichen Disziplinen gut lesbaren Aoeberblick A1/4ber den Stand der Forschung zur monetAren Integration im allgemeinen und zur europAischen WAhrungsintegration im besonderen. Es gibt darA1/4ber hinaus Anregungen fA1/4r weiterfA1/4hrende Untersuchungen, z.B. zur Rolle der Arbeitsmarktverfassungen oder der Fiskal- und der Sozialpolitik.

Data Warehousing und Data Mining - Eine Einfuhrung in entscheidungsunterstutzende Systeme (German, Paperback, 2. uberarb. u.... Data Warehousing und Data Mining - Eine Einfuhrung in entscheidungsunterstutzende Systeme (German, Paperback, 2. uberarb. u. erw. Aufl. 2002)
Markus Lusti
R1,203 Discovery Miles 12 030 Ships in 10 - 15 working days

Im Mittelpunkt dieses anwendungsbezogenen Lehrbuchs stehen Architekturen, Methoden und Werkzeuge entscheidungsunterstutzender Systeme. Beispiele und Aufgaben ermoglichen die Entwicklung von Anwendungen mit der Demonstrationssoftware der CD ROM. Eine interaktive Foliensammlung veranschaulicht den Buchtext und verweist auf zusatzliches Lernmaterial. Der erste Teil stellt mit der Nutzwertanalyse (AHP) und Was-Wenn-Analysen traditionelle entscheidungsunterstutzende Ansatze dar und fuhrt anhand regelbasierter Systeme in wissensbasierte Systeme ein. Der zweite und dritte Teil behandeln das Schwerpunktthema Data Warehousing und Data Mining. Data Warehousing und OLAP bereiten die Inhalte von Produktionsdatenbanken fur Abfragen und Analysen durch Endbenutzer auf. Nach einem Uberblick uber die wichtigsten Data Mining-Verfahren konzentriert sich der dritte Teil auf zwei der verbreitesten Methoden, die Regelinduktion und neuronale Netze."

The Enrichment Game - A Story About Making Data Powerful (Paperback): Doug Needham The Enrichment Game - A Story About Making Data Powerful (Paperback)
Doug Needham
R937 R799 Discovery Miles 7 990 Save R138 (15%) Ships in 10 - 15 working days
Simplifying Data Engineering and Analytics with Delta - Create analytics-ready data that fuels artificial intelligence and... Simplifying Data Engineering and Analytics with Delta - Create analytics-ready data that fuels artificial intelligence and business intelligence (Paperback)
Anindita Mahapatra, Doug May
R1,146 Discovery Miles 11 460 Ships in 10 - 15 working days

Explore how Delta brings reliability, performance, and governance to your data lake and all the AI and BI use cases built on top of it Key Features Learn Delta's core concepts and features as well as what makes it a perfect match for data engineering and analysis Solve business challenges of different industry verticals using a scenario-based approach Make optimal choices by understanding the various tradeoffs provided by Delta Book DescriptionDelta helps you generate reliable insights at scale and simplifies architecture around data pipelines, allowing you to focus primarily on refining the use cases being worked on. This is especially important when you consider that existing architecture is frequently reused for new use cases. In this book, you'll learn about the principles of distributed computing, data modeling techniques, and big data design patterns and templates that help solve end-to-end data flow problems for common scenarios and are reusable across use cases and industry verticals. You'll also learn how to recover from errors and the best practices around handling structured, semi-structured, and unstructured data using Delta. After that, you'll get to grips with features such as ACID transactions on big data, disciplined schema evolution, time travel to help rewind a dataset to a different time or version, and unified batch and streaming capabilities that will help you build agile and robust data products. By the end of this Delta book, you'll be able to use Delta as the foundational block for creating analytics-ready data that fuels all AI/BI use cases. What you will learn Explore the key challenges of traditional data lakes Appreciate the unique features of Delta that come out of the box Address reliability, performance, and governance concerns using Delta Analyze the open data format for an extensible and pluggable architecture Handle multiple use cases to support BI, AI, streaming, and data discovery Discover how common data and machine learning design patterns are executed on Delta Build and deploy data and machine learning pipelines at scale using Delta Who this book is forData engineers, data scientists, ML practitioners, BI analysts, or anyone in the data domain working with big data will be able to put their knowledge to work with this practical guide to executing pipelines and supporting diverse use cases using the Delta protocol. Basic knowledge of SQL, Python programming, and Spark is required to get the most out of this book.

Democratizing Artificial Intelligence with UiPath - Expand automation in your organization to achieve operational efficiency... Democratizing Artificial Intelligence with UiPath - Expand automation in your organization to achieve operational efficiency and high performance (Paperback)
Fanny Ip, Jeremiah Crowley, Tom Torlone
R1,321 Discovery Miles 13 210 Ships in 10 - 15 working days

Build an end-to-end business solution in the cognitive automation lifecycle and explore UiPath Document Understanding, UiPath AI Center, and Druid Key Features Explore out-of-the-box (OOTB) AI Models in UiPath Learn how to deploy, manage, and continuously improve machine learning models using UiPath AI Center Deploy UiPath-integrated chatbots and master UiPath Document Understanding Book DescriptionArtificial intelligence (AI) enables enterprises to optimize business processes that are probabilistic, highly variable, and require cognitive abilities with unstructured data. Many believe there is a steep learning curve with AI, however, the goal of our book is to lower the barrier to using AI. This practical guide to AI with UiPath will help RPA developers and tech-savvy business users learn how to incorporate cognitive abilities into business process optimization. With the hands-on approach of this book, you'll quickly be on your way to implementing cognitive automation to solve everyday business problems. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will help you understand the power of AI and give you an overview of the relevant out-of-the-box models. You'll learn about cognitive AI in the context of RPA, the basics of machine learning, and how to apply cognitive automation within the development lifecycle. You'll then put your skills to test by building three use cases with UiPath Document Understanding, UiPath AI Center, and Druid. By the end of this AI book, you'll be able to build UiPath automations with the cognitive capabilities of intelligent document processing, machine learning, and chatbots, while understanding the development lifecycle. What you will learn Discover how to bridge the gap between RPA and cognitive automation Understand how to configure, deploy, and maintain ML models in UiPath Explore OOTB models to manage documents, chats, emails, and more Prepare test data and test cases for user acceptance testing (UAT) Build a UiPath automation to act upon Druid responses Find out how to connect custom models to RPA Who this book is forAI Engineers and RPA developers who want to upskill and deploy out-of-the-box models using UiPath's AI capabilities will find this guide useful. A basic understanding of robotic process automation and machine learning will be beneficial but not mandatory to get started with this UiPath book.

Analytical Puzzle - Profitable Data Warehousing, Business Intelligence & Analytics (Paperback): David Haertzen Analytical Puzzle - Profitable Data Warehousing, Business Intelligence & Analytics (Paperback)
David Haertzen
R1,158 R1,004 Discovery Miles 10 040 Save R154 (13%) Ships in 12 - 19 working days

Do you enjoy completing puzzles? Perhaps one of the most challenging (yet rewarding) puzzles is delivering a successful data warehouse suitable for data mining and analytics. The Analytical Puzzle describes an unbiased, practical, and comprehensive approach to building a data warehouse which will lead to an increased level of business intelligence within your organisation. New technologies continuously impact this approach and therefore this book explains how to leverage big data, cloud computing, data warehouse appliances, data mining, predictive analytics, data visualisation and mobile devices. This book describes an unbiased, practical, and comprehensive approach to building a data warehouse which will lead to an increased level of business intelligence within your organisation. New technologies continuously impact this approach and therefore this book explains how to leverage big data, cloud computing, data warehouse appliances, data mining, predictive analytics, data visualisation and mobile devices.

Introduction to Data Platforms - How to leverage data fabric concepts to engineer your organization's data for... Introduction to Data Platforms - How to leverage data fabric concepts to engineer your organization's data for today's cloud-based digital world (Paperback)
Anthonydavid Giordano
R602 R551 Discovery Miles 5 510 Save R51 (8%) Ships in 10 - 15 working days
Hands-on Kubernetes on Azure - Use Azure Kubernetes Service to automate management, scaling, and deployment of containerized... Hands-on Kubernetes on Azure - Use Azure Kubernetes Service to automate management, scaling, and deployment of containerized applications, 3rd Edition (Paperback, 3rd Revised edition)
Nills Franssens, Shivakumar Gopalakrishnan, Gunther Lenz
R1,321 Discovery Miles 13 210 Ships in 10 - 15 working days

Understand the fundamentals of Kubernetes deployment on Azure with a learn-by-doing approach Key Features Get to grips with the fundamentals of containers and Kubernetes Deploy containerized applications using the Kubernetes platform Learn how you can scale your workloads and secure your application running in Azure Kubernetes Service Book DescriptionContainers and Kubernetes containers facilitate cloud deployments and application development by enabling efficient versioning with improved security and portability. With updated chapters on role-based access control, pod identity, storing secrets, and network security in AKS, this third edition begins by introducing you to containers, Kubernetes, and Azure Kubernetes Service (AKS), and guides you through deploying an AKS cluster in different ways. You will then delve into the specifics of Kubernetes by deploying a sample guestbook application on AKS and installing complex Kubernetes apps using Helm. With the help of real-world examples, you'll also get to grips with scaling your applications and clusters. As you advance, you'll learn how to overcome common challenges in AKS and secure your applications with HTTPS. You will also learn how to secure your clusters and applications in a dedicated section on security. In the final section, you'll learn about advanced integrations, which give you the ability to create Azure databases and run serverless functions on AKS as well as the ability to integrate AKS with a continuous integration and continuous delivery (CI/CD) pipeline using GitHub Actions. By the end of this Kubernetes book, you will be proficient in deploying containerized workloads on Microsoft Azure with minimal management overhead. What you will learn Plan, configure, and run containerized applications in production. Use Docker to build applications in containers and deploy them on Kubernetes. Monitor the AKS cluster and the application. Monitor your infrastructure and applications in Kubernetes using Azure Monitor. Secure your cluster and applications using Azure-native security tools. Connect an app to the Azure database. Store your container images securely with Azure Container Registry. Install complex Kubernetes applications using Helm. Integrate Kubernetes with multiple Azure PaaS services, such as databases, Azure Security Center, and Functions. Use GitHub Actions to perform continuous integration and continuous delivery to your cluster. Who this book is forIf you are an aspiring DevOps professional, system administrator, developer, or site reliability engineer interested in learning how to get the most out of containers and Kubernetes, then this book is for you.

Azure Data Engineering Cookbook - Get well versed in various data engineering techniques in Azure using this recipe-based guide... Azure Data Engineering Cookbook - Get well versed in various data engineering techniques in Azure using this recipe-based guide (Paperback, 2nd Revised edition)
Nagaraj Venkatesan, Ahmad Osama
R1,256 Discovery Miles 12 560 Ships in 10 - 15 working days

Nearly 80 recipes to help you collect and transform data from multiple sources into a single data source, making it way easier to perform analytics on the data Key Features Build data pipelines from scratch and find solutions to common data engineering problems Learn how to work with Azure Data Factory, Data Lake, Databricks, and Synapse Analytics Monitor and maintain your data engineering pipelines using Log Analytics, Azure Monitor, and Azure Purview Book DescriptionThe famous quote 'Data is the new oil' seems more true every day as the key to most organizations' long-term success lies in extracting insights from raw data. One of the major challenges organizations face in leveraging value out of data is building performant data engineering pipelines for data visualization, ingestion, storage, and processing. This second edition of the immensely successful book by Ahmad Osama brings to you several recent enhancements in Azure data engineering and shares approximately 80 useful recipes covering common scenarios in building data engineering pipelines in Microsoft Azure. You'll explore recipes from Azure Synapse Analytics workspaces Gen 2 and get to grips with Synapse Spark pools, SQL Serverless pools, Synapse integration pipelines, and Synapse data flows. You'll also understand Synapse SQL Pool optimization techniques in this second edition. Besides Synapse enhancements, you'll discover helpful tips on managing Azure SQL Database and learn about security, high availability, and performance monitoring. Finally, the book takes you through overall data engineering pipeline management, focusing on monitoring using Log Analytics and tracking data lineage using Azure Purview. By the end of this book, you'll be able to build superior data engineering pipelines along with having an invaluable go-to guide. What you will learn Process data using Azure Databricks and Azure Synapse Analytics Perform data transformation using Azure Synapse data flows Perform common administrative tasks in Azure SQL Database Build effective Synapse SQL pools which can be consumed by Power BI Monitor Synapse SQL and Spark pools using Log Analytics Track data lineage using Microsoft Purview integration with pipelines Who this book is forThis book is for data engineers, data architects, database administrators, and data professionals who want to get well versed with the Azure data services for building data pipelines. Basic understanding of cloud and data engineering concepts will help in getting the most out of this book.

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