Download or read book Data Modeling for Azure Data Services written by Peter ter Braake and published by Packt Publishing Ltd. This book was released on 2021-07-30 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Choose the right Azure data service and correct model design for successful implementation of your data model with the help of this hands-on guide Key FeaturesDesign a cost-effective, performant, and scalable database in AzureChoose and implement the most suitable design for a databaseDiscover how your database can scale with growing data volumes, concurrent users, and query complexityBook Description Data is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation. Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory. By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution. What you will learnModel relational database using normalization, dimensional, or Data Vault modelingProvision and implement Azure SQL DB and Azure Synapse SQL PoolsDiscover how to model a Data Lake and implement it using Azure StorageModel a NoSQL database and provision and implement an Azure Cosmos DBUse Azure Data Factory to implement ETL/ELT processesCreate a star schema model using dimensional modelingWho this book is for This book is for business intelligence developers and consultants who work on (modern) cloud data warehousing and design and implement databases. Beginner-level knowledge of cloud data management is expected.

Download or read book Tabular Modeling in Microsoft SQL Server Analysis Services written by Marco Russo and published by Microsoft Press. This book was released on 2017-04-12 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build agile and responsive business intelligence solutions Create a semantic model and analyze data using the tabular model in SQL Server 2016 Analysis Services to create corporate-level business intelligence (BI) solutions. Led by two BI experts, you will learn how to build, deploy, and query a tabular model by following detailed examples and best practices. This hands-on book shows you how to use the tabular model’s in-memory database to perform rapid analytics—whether you are new to Analysis Services or already familiar with its multidimensional model. Discover how to: • Determine when a tabular or multidimensional model is right for your project • Build a tabular model using SQL Server Data Tools in Microsoft Visual Studio 2015 • Integrate data from multiple sources into a single, coherent view of company information • Choose a data-modeling technique that meets your organization’s performance and usability requirements • Implement security by establishing administrative and data user roles • Define and implement partitioning strategies to reduce processing time • Use Tabular Model Scripting Language (TMSL) to execute and automate administrative tasks • Optimize your data model to reduce the memory footprint for VertiPaq • Choose between in-memory (VertiPaq) and pass-through (DirectQuery) engines for tabular models • Select the proper hardware and virtualization configurations • Deploy and manipulate tabular models from C# and PowerShell using AMO and TOM libraries Get code samples, including complete apps, at: https://aka.ms/tabular/downloads About This Book • For BI professionals who are new to SQL Server 2016 Analysis Services or already familiar with previous versions of the product, and who want the best reference for creating and maintaining tabular models. • Assumes basic familiarity with database design and business analytics concepts.

Download or read book Data Engineering on Azure written by Vlad Riscutia and published by Simon and Schuster. This book was released on 2021-08-17 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure. Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data

Download or read book Cloud Data Design Orchestration and Management Using Microsoft Azure written by Francesco Diaz and published by Apress. This book was released on 2018-06-28 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Microsoft Azure to optimally design your data solutions and save time and money. Scenarios are presented covering analysis, design, integration, monitoring, and derivatives. This book is about data and provides you with a wide range of possibilities to implement a data solution on Azure, from hybrid cloud to PaaS services. Migration from existing solutions is presented in detail. Alternatives and their scope are discussed. Five of six chapters explore PaaS, while one focuses on SQL Server features for cloud and relates to hybrid cloud and IaaS functionalities. What You'll Learn Know the Azure services useful to implement a data solution Match the products/services used to your specific needs Fit relational databases efficiently into data design Understand how to work with any type of data using Azure hybrid and public cloud features Use non-relational alternatives to solve even complex requirements Orchestrate data movement using Azure services Approach analysis and manipulation according to the data life cycle Who This Book Is For Software developers and professionals with a good data design background and basic development skills who want to learn how to implement a solution using Azure data services

Download or read book Azure Data Engineering Cookbook written by Ahmad Osama and published by Packt Publishing Ltd. This book was released on 2021-04-05 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 90 recipes to help you orchestrate modern ETL/ELT workflows and perform analytics using Azure services more easily Key FeaturesBuild highly efficient ETL pipelines using the Microsoft Azure Data servicesCreate and execute real-time processing solutions using Azure Databricks, Azure Stream Analytics, and Azure Data ExplorerDesign and execute batch processing solutions using Azure Data FactoryBook Description Data engineering is one of the faster growing job areas as Data Engineers are the ones who ensure that the data is extracted, provisioned and the data is of the highest quality for data analysis. This book uses various Azure services to implement and maintain infrastructure to extract data from multiple sources, and then transform and load it for data analysis. It takes you through different techniques for performing big data engineering using Microsoft Azure Data services. It begins by showing you how Azure Blob storage can be used for storing large amounts of unstructured data and how to use it for orchestrating a data workflow. You'll then work with different Cosmos DB APIs and Azure SQL Database. Moving on, you'll discover how to provision an Azure Synapse database and find out how to ingest and analyze data in Azure Synapse. As you advance, you'll cover the design and implementation of batch processing solutions using Azure Data Factory, and understand how to manage, maintain, and secure Azure Data Factory pipelines. You'll also design and implement batch processing solutions using Azure Databricks and then manage and secure Azure Databricks clusters and jobs. In the concluding chapters, you'll learn how to process streaming data using Azure Stream Analytics and Data Explorer. By the end of this Azure book, you'll have gained the knowledge you need to be able to orchestrate batch and real-time ETL workflows in Microsoft Azure. What you will learnUse Azure Blob storage for storing large amounts of unstructured dataPerform CRUD operations on the Cosmos Table APIImplement elastic pools and business continuity with Azure SQL DatabaseIngest and analyze data using Azure Synapse AnalyticsDevelop Data Factory data flows to extract data from multiple sourcesManage, maintain, and secure Azure Data Factory pipelinesProcess streaming data using Azure Stream Analytics and Data ExplorerWho this book is for This book is for Data Engineers, Database administrators, Database developers, and extract, load, transform (ETL) developers looking to build expertise in Azure Data engineering using a recipe-based approach. Technical architects and database architects with experience in designing data or ETL applications either on-premise or on any other cloud vendor who wants to learn Azure Data engineering concepts will also find this book useful. Prior knowledge of Azure fundamentals and data engineering concepts is needed.

Download or read book Expert Data Modeling with Power BI written by Soheil Bakhshi and published by Packt Publishing Ltd. This book was released on 2021-06-11 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Manage and work with business data effectively by learning data modeling techniques and leveraging the latest features of Power BI Key Features Understand data modeling techniques to get the best out of data using Power BI Define the relationships between data to extract valuable insights Solve a wide variety of business challenges by building optimal data models Book DescriptionThis book is a comprehensive guide to understanding the ins and outs of data modeling and how to create data models using Power BI confidently. You'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. In this book, you'll explore how to use data modeling and navigation techniques to define relationships and create a data model before defining new metrics and performing custom calculations using modeling features. As you advance through the chapters, the book will demonstrate how to create full-fledged data models, enabling you to create efficient data models and simpler DAX code with new data modeling features. With the help of examples, you'll discover how you can solve business challenges by building optimal data models and changing your existing data models to meet evolving business requirements. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support reporting and data analytics.What you will learn Implement virtual tables and time intelligence functionalities in DAX to build a powerful model Identify Dimension and Fact tables and implement them in Power Query Editor Deal with advanced data preparation scenarios while building Star Schema Explore best practices for data preparation and modeling Discover different hierarchies and their common pitfalls Understand complex data models and how to decrease the level of model complexity with different approaches Learn advanced data modeling techniques such as aggregations, incremental refresh, and RLS/OLS Who this book is for This MS Power BI book is for BI users, data analysts, and analysis developers who want to become well-versed with data modeling techniques to make the most of Power BI. You’ll need a solid grasp on basic use cases and functionalities of Power BI and Star Schema functionality before you can dive in.

Download or read book Cloud Scale Analytics with Azure Data Services written by Patrik Borosch and published by Packt Publishing Ltd. This book was released on 2021-07-23 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to implementing a scalable and fast state-of-the-art analytical data estate Key FeaturesStore and analyze data with enterprise-grade security and auditingPerform batch, streaming, and interactive analytics to optimize your big data solutions with easeDevelop and run parallel data processing programs using real-world enterprise scenariosBook Description Azure Data Lake, the modern data warehouse architecture, and related data services on Azure enable organizations to build their own customized analytical platform to fit any analytical requirements in terms of volume, speed, and quality. This book is your guide to learning all the features and capabilities of Azure data services for storing, processing, and analyzing data (structured, unstructured, and semi-structured) of any size. You will explore key techniques for ingesting and storing data and perform batch, streaming, and interactive analytics. The book also shows you how to overcome various challenges and complexities relating to productivity and scaling. Next, you will be able to develop and run massive data workloads to perform different actions. Using a cloud-based big data-modern data warehouse-analytics setup, you will also be able to build secure, scalable data estates for enterprises. Finally, you will not only learn how to develop a data warehouse but also understand how to create enterprise-grade security and auditing big data programs. By the end of this Azure book, you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs. What you will learnImplement data governance with Azure servicesUse integrated monitoring in the Azure Portal and integrate Azure Data Lake Storage into the Azure MonitorExplore the serverless feature for ad-hoc data discovery, logical data warehousing, and data wranglingImplement networking with Synapse Analytics and Spark poolsCreate and run Spark jobs with Databricks clustersImplement streaming using Azure Functions, a serverless runtime environment on AzureExplore the predefined ML services in Azure and use them in your appWho this book is for This book is for data architects, ETL developers, or anyone who wants to get well-versed with Azure data services to implement an analytical data estate for their enterprise. The book will also appeal to data scientists and data analysts who want to explore all the capabilities of Azure data services, which can be used to store, process, and analyze any kind of data. A beginner-level understanding of data analysis and streaming will be required.

Download or read book The Microsoft Data Warehouse Toolkit written by Joy Mundy and published by John Wiley & Sons. This book was released on 2007-03-22 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: This groundbreaking book is the first in the Kimball Toolkit series to be product-specific. Microsoft’s BI toolset has undergone significant changes in the SQL Server 2005 development cycle. SQL Server 2005 is the first viable, full-functioned data warehouse and business intelligence platform to be offered at a price that will make data warehousing and business intelligence available to a broad set of organizations. This book is meant to offer practical techniques to guide those organizations through the myriad of challenges to true success as measured by contribution to business value. Building a data warehousing and business intelligence system is a complex business and engineering effort. While there are significant technical challenges to overcome in successfully deploying a data warehouse, the authors find that the most common reason for data warehouse project failure is insufficient focus on the business users and business problems. In an effort to help people gain success, this book takes the proven Business Dimensional Lifecycle approach first described in best selling The Data Warehouse Lifecycle Toolkit and applies it to the Microsoft SQL Server 2005 tool set. Beginning with a thorough description of how to gather business requirements, the book then works through the details of creating the target dimensional model, setting up the data warehouse infrastructure, creating the relational atomic database, creating the analysis services databases, designing and building the standard report set, implementing security, dealing with metadata, managing ongoing maintenance and growing the DW/BI system. All of these steps tie back to the business requirements. Each chapter describes the practical steps in the context of the SQL Server 2005 platform. Intended Audience The target audience for this book is the IT department or service provider (consultant) who is: Planning a small to mid-range data warehouse project; Evaluating or planning to use Microsoft technologies as the primary or exclusive data warehouse server technology; Familiar with the general concepts of data warehousing and business intelligence. The book will be directed primarily at the project leader and the warehouse developers, although everyone involved with a data warehouse project will find the book useful. Some of the book’s content will be more technical than the typical project leader will need; other chapters and sections will focus on business issues that are interesting to a database administrator or programmer as guiding information. The book is focused on the mass market, where the volume of data in a single application or data mart is less than 500 GB of raw data. While the book does discuss issues around handling larger warehouses in the Microsoft environment, it is not exclusively, or even primarily, concerned with the unusual challenges of extremely large datasets. About the Authors JOY MUNDY has focused on data warehousing and business intelligence since the early 1990s, specializing in business requirements analysis, dimensional modeling, and business intelligence systems architecture. Joy co-founded InfoDynamics LLC, a data warehouse consulting firm, then joined Microsoft WebTV to develop closed-loop analytic applications and a packaged data warehouse. Before returning to consulting with the Kimball Group in 2004, Joy worked in Microsoft SQL Server product development, managing a team that developed the best practices for building business intelligence systems on the Microsoft platform. Joy began her career as a business analyst in banking and finance. She graduated from Tufts University with a BA in Economics, and from Stanford with an MS in Engineering Economic Systems. WARREN THORNTHWAITE has been building data warehousing and business intelligence systems since 1980. Warren worked at Metaphor for eight years, where he managed the consulting organization and implemented many major data warehouse systems. After Metaphor, Warren managed the enterprise-wide data warehouse development at Stanford University. He then co-founded InfoDynamics LLC, a data warehouse consulting firm, with his co-author, Joy Mundy. Warren joined up with WebTV to help build a world class, multi-terabyte customer focused data warehouse before returning to consulting with the Kimball Group. In addition to designing data warehouses for a range of industries, Warren speaks at major industry conferences and for leading vendors, and is a long-time instructor for Kimball University. Warren holds an MBA in Decision Sciences from the University of Pennsylvania's Wharton School, and a BA in Communications Studies from the University of Michigan. RALPH KIMBALL, PH.D., has been a leading visionary in the data warehouse industry since 1982 and is one of today's most internationally well-known authors, speakers, consultants, and teachers on data warehousing. He writes the "Data Warehouse Architect" column for Intelligent Enterprise (formerly DBMS) magazine.

Download or read book Azure Data Factory Cookbook written by Dmitry Anoshin and published by Packt Publishing Ltd. This book was released on 2020-12-24 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve real-world data problems and create data-driven workflows for easy data movement and processing at scale with Azure Data Factory Key FeaturesLearn how to load and transform data from various sources, both on-premises and on cloudUse Azure Data Factory’s visual environment to build and manage hybrid ETL pipelinesDiscover how to prepare, transform, process, and enrich data to generate key insightsBook Description Azure Data Factory (ADF) is a modern data integration tool available on Microsoft Azure. This Azure Data Factory Cookbook helps you get up and running by showing you how to create and execute your first job in ADF. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines. This book will help you to discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage, which are frequently used for big data analytics. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premise infrastructure with cloud-native tools to get relevant business insights. As you advance, you’ll be able to integrate the most commonly used Azure Services into ADF and understand how Azure services can be useful in designing ETL pipelines. The book will take you through the common errors that you may encounter while working with ADF and show you how to use the Azure portal to monitor pipelines. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF. By the end of this book, you’ll be able to use ADF as the main ETL and orchestration tool for your data warehouse or data platform projects. What you will learnCreate an orchestration and transformation job in ADFDevelop, execute, and monitor data flows using Azure SynapseCreate big data pipelines using Azure Data Lake and ADFBuild a machine learning app with Apache Spark and ADFMigrate on-premises SSIS jobs to ADFIntegrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure FunctionsRun big data compute jobs within HDInsight and Azure DatabricksCopy data from AWS S3 and Google Cloud Storage to Azure Storage using ADF's built-in connectorsWho this book is for This book is for ETL developers, data warehouse and ETL architects, software professionals, and anyone who wants to learn about the common and not-so-common challenges faced while developing traditional and hybrid ETL solutions using Microsoft's Azure Data Factory. You’ll also find this book useful if you are looking for recipes to improve or enhance your existing ETL pipelines. Basic knowledge of data warehousing is expected.

Download or read book Basics of Power BI Modeling written by Reza Rad and published by RADACAD Systems Limited. This book was released on 2020-09-11 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: I have been dealing with many Power BI challenges in my professional life as a Power BI consultant and a trainer. Challenges normally come as calculation or DAX questions, or sometimes as a performance question. However, after digging deeper into the problem, soon, it will be revealed that the problem is related to a more fundamental challenge; data modeling.If you have a Power BI implementation with many calculation-related or performance-related issues, I strongly suggest looking into your data model because that is where most of the problems start.A good data model is a great base, which upon that, you can build up many stories of calculations and analysis. A bad data model causes problems on every level that you add upon it, and might sometime cause the whole solution to collapse.Fortunately, data modeling is not rocket science. I explained the basic principles of the data modeling with examples in this book. Use this book as the learning path towards a better data model. Most of the tips mentioned in this book are product-agnostic (such as star-schema, dimension, and fact tables). However, this book is particularly designed and developed for a Power BI product user.This book is for you if you are building a Power BI solution. If your task is only visualizing the existing data, this book might not be needed for you. However, What I have seen in many cases, is that the requirement starts with just visualize the data, and then more data tables appear, and you get into the tunnel of data modeling without knowing the principles of it. This book is a guide for you through that tunnel.

Download or read book Exam Ref 70 767 Implementing a SQL Data Warehouse written by Jose Chinchilla and published by Microsoft Press. This book was released on 2017-11-09 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare for Microsoft Exam 70-767–and help demonstrate your real-world mastery of skills for managing data warehouses. This exam is intended for Extract, Transform, Load (ETL) data warehouse developers who create business intelligence (BI) solutions. Their responsibilities include data cleansing as well as ETL and data warehouse implementation. The reader should have experience installing and implementing a Master Data Services (MDS) model, using MDS tools, and creating a Master Data Manager database and web application. The reader should understand how to design and implement ETL control flow elements and work with a SQL Service Integration Services package. Focus on the expertise measured by these objectives: • Design, and implement, and maintain a data warehouse • Extract, transform, and load data • Build data quality solutionsThis Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you have working knowledge of relational database technology and incremental database extraction, as well as experience with designing ETL control flows, using and debugging SSIS packages, accessing and importing or exporting data from multiple sources, and managing a SQL data warehouse. Implementing a SQL Data Warehouse About the Exam Exam 70-767 focuses on skills and knowledge required for working with relational database technology. About Microsoft Certification Passing this exam earns you credit toward a Microsoft Certified Professional (MCP) or Microsoft Certified Solutions Associate (MCSA) certification that demonstrates your mastery of data warehouse management Passing this exam as well as Exam 70-768 (Developing SQL Data Models) earns you credit toward a Microsoft Certified Solutions Associate (MCSA) SQL 2016 Business Intelligence (BI) Development certification. See full details at: microsoft.com/learning

Download or read book Guide to NoSQL with Azure Cosmos DB written by Gaston C. Hillar and published by Packt Publishing Ltd. This book was released on 2018-09-28 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows you how to develop applications that work with Azure Cosmos DB. Azure and other cloud applications typically work with massive amounts of data that can be organized in different ways. These applications will often require elastic scale out of storage and throughput, and to work across new geographical regions. This is the ...

Download or read book The Modern Data Warehouse in Azure written by Matt How and published by Apress. This book was released on 2020-06-15 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a modern data warehouse on Microsoft's Azure Platform that is flexible, adaptable, and fast—fast to snap together, reconfigure, and fast at delivering results to drive good decision making in your business. Gone are the days when data warehousing projects were lumbering dinosaur-style projects that took forever, drained budgets, and produced business intelligence (BI) just in time to tell you what to do 10 years ago. This book will show you how to assemble a data warehouse solution like a jigsaw puzzle by connecting specific Azure technologies that address your own needs and bring value to your business. You will see how to implement a range of architectural patterns using batches, events, and streams for both data lake technology and SQL databases. You will discover how to manage metadata and automation to accelerate the development of your warehouse while establishing resilience at every level. And you will know how to feed downstream analytic solutions such as Power BI and Azure Analysis Services to empower data-driven decision making that drives your business forward toward a pattern of success. This book teaches you how to employ the Azure platform in a strategy to dramatically improve implementation speed and flexibility of data warehousing systems. You will know how to make correct decisions in design, architecture, and infrastructure such as choosing which type of SQL engine (from at least three options) best meets the needs of your organization. You also will learn about ETL/ELT structure and the vast number of accelerators and patterns that can be used to aid implementation and ensure resilience. Data warehouse developers and architects will find this book a tremendous resource for moving their skills into the future through cloud-based implementations. What You Will LearnChoose the appropriate Azure SQL engine for implementing a given data warehouse Develop smart, reusable ETL/ELT processes that are resilient and easily maintained Automate mundane development tasks through tools such as PowerShell Ensure consistency of data by creating and enforcing data contracts Explore streaming and event-driven architectures for data ingestionCreate advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse Who This Book Is For Data warehouse or ETL/ELT developers who wish to implement a data warehouse project in the Azure cloud, and developers currently working in on-premise environments who want to move to the cloud, and for developers with Azure experience looking to tighten up their implementation and consolidate their knowledge

Download or read book The Data Warehouse Toolkit written by Ralph Kimball and published by John Wiley & Sons. This book was released on 2011-08-08 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.

Download or read book Hands On Data Warehousing with Azure Data Factory written by Christian Coté and published by Packt Publishing Ltd. This book was released on 2018-05-31 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of Microsoft Azure Data Factory v2 to build hybrid data solutions Key Features Combine the power of Azure Data Factory v2 and SQL Server Integration Services Design and enhance performance and scalability of a modern ETL hybrid solution Interact with the loaded data in data warehouse and data lake using Power BI Book Description ETL is one of the essential techniques in data processing. Given data is everywhere, ETL will always be the vital process to handle data from different sources. Hands-On Data Warehousing with Azure Data Factory starts with the basic concepts of data warehousing and ETL process. You will learn how Azure Data Factory and SSIS can be used to understand the key components of an ETL solution. You will go through different services offered by Azure that can be used by ADF and SSIS, such as Azure Data Lake Analytics, Machine Learning and Databrick’s Spark with the help of practical examples. You will explore how to design and implement ETL hybrid solutions using different integration services with a step-by-step approach. Once you get to grips with all this, you will use Power BI to interact with data coming from different sources in order to reveal valuable insights. By the end of this book, you will not only learn how to build your own ETL solutions but also address the key challenges that are faced while building them. What you will learn Understand the key components of an ETL solution using Azure Data Factory and Integration Services Design the architecture of a modern ETL hybrid solution Implement ETL solutions for both on-premises and Azure data Improve the performance and scalability of your ETL solution Gain thorough knowledge of new capabilities and features added to Azure Data Factory and Integration Services Who this book is for This book is for you if you are a software professional who develops and implements ETL solutions using Microsoft SQL Server or Azure cloud. It will be an added advantage if you are a software engineer, DW/ETL architect, or ETL developer, and know how to create a new ETL implementation or enhance an existing one with ADF or SSIS.

Download or read book Analyzing Data with Power BI and Power Pivot for Excel written by Alberto Ferrari and published by Microsoft Press. This book was released on 2017-04-28 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness. How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It’s meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way–like experienced data modelers do. As you’ll soon see, with the right data model, the correct answer is always a simple one! By reading this book, you will: • Gain an understanding of the basics of data modeling, including tables, relationships, and keys • Familiarize yourself with star schemas, snowflakes, and common modeling techniques • Learn the importance of granularity • Discover how to use multiple fact tables, like sales and purchases, in a complex data model • Manage calendar-related calculations by using date tables • Track historical attributes, like previous addresses of customers or manager assignments • Use snapshots to compute quantity on hand • Work with multiple currencies in the most efficient way • Analyze events that have durations, including overlapping durations • Learn what data model you need to answer your specific business questions About This Book • For Excel and Power BI users who want to exploit the full power of their favorite tools • For BI professionals seeking new ideas for modeling data

Download or read book Limitless Analytics with Azure Synapse written by Prashant Kumar Mishra and published by Packt Publishing Ltd. This book was released on 2021-06-18 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the Azure analytics platform's key analytics services to deliver unmatched intelligence for your data Key FeaturesLearn to ingest, prepare, manage, and serve data for immediate business requirementsBring enterprise data warehousing and big data analytics together to gain insights from your dataDevelop end-to-end analytics solutions using Azure SynapseBook Description Azure Synapse Analytics, which Microsoft describes as the next evolution of Azure SQL Data Warehouse, is a limitless analytics service that brings enterprise data warehousing and big data analytics together. With this book, you'll learn how to discover insights from your data effectively using this platform. The book starts with an overview of Azure Synapse Analytics, its architecture, and how it can be used to improve business intelligence and machine learning capabilities. Next, you'll go on to choose and set up the correct environment for your business problem. You'll also learn a variety of ways to ingest data from various sources and orchestrate the data using transformation techniques offered by Azure Synapse. Later, you'll explore how to handle both relational and non-relational data using the SQL language. As you progress, you'll perform real-time streaming and execute data analysis operations on your data using various languages, before going on to apply ML techniques to derive accurate and granular insights from data. Finally, you'll discover how to protect sensitive data in real time by using security and privacy features. By the end of this Azure book, you'll be able to build end-to-end analytics solutions while focusing on data prep, data management, data warehousing, and AI tasks. What you will learnExplore the necessary considerations for data ingestion and orchestration while building analytical pipelinesUnderstand pipelines and activities in Synapse pipelines and use them to construct end-to-end data-driven workflowsQuery data using various coding languages on Azure SynapseFocus on Synapse SQL and Synapse SparkManage and monitor resource utilization and query activity in Azure SynapseConnect Power BI workspaces with Azure Synapse and create or modify reports directly from Synapse StudioCreate and manage IP firewall rules in Azure SynapseWho this book is for This book is for data architects, data scientists, data engineers, and business analysts who are looking to get up and running with the Azure Synapse Analytics platform. Basic knowledge of data warehousing will be beneficial to help you understand the concepts covered in this book more effectively.