Dmitry Anoshin – författare

Build world-class enterprise Business Intelligence solutions with MicroStrategy 10Key Features[*] Fix the gap between BI tools and implementation/integration processes with big data and predictive analytics using this comprehensive guide to MicroStrategy 10[*] Highly practical, example-rich guide that lets you implement business intelligence with MicroStrategy 10 in your organization[*] Create the best user experience with BI dashboards using MicroStrategy using this up-to-date, comprehensive guideBook DescriptionBusiness intelligence is becoming more important by the day, with cloud offerings and mobile devices gaining wider acceptance and achieving better market penetration. MicroStrategy Reporting Suite is an absolute leader in the BI market and offers rich capabilities from basic data visualizations to predictive analytics. It lets you various delivery methods such as the Web, desktops, and mobiles.Using real-world BI scenarios, this book helps you to implement Business Analytics solutions in big e-commerce companies. It kicks off with MicroStrategy 10 features and then covers schema design models and techniques. Building upon your existing knowledge, the book will teach you advanced techniques for building documents and dashboards. It further teaches various graphical techniques for presenting data for analysis using maps, graphs, and advanced charts. Although MicroStrategy has rich functionality, the book will show how to customize it in order to meet your business requirements. You will also become familiar with the native analytical functions that will help you to maximize the impact of BI solutions with powerful predictive analytics. Furthermore, the book will focus on MicroStrategy Mobile Analytics along with data discovery and desktop capabilities such as connecting various data sources and building interactive dashboards. The book will also uncover best practices, troubleshooting techniques for MicroStrategy system administration, and also security and authentication techniques. Lastly, you will learn to use Hadoop for MicroStrategy reporting.By the end of the book, you will become proficient in evaluating any BI software in order to choose the best one that meets all business requirements.What you will learn[*] Explore various visualization techniques for presenting analyzed data[*] Customize MicroStrategy in order to meet your business requirements[*] Develop and design mobile dashboards[*] Use the advanced techniques such as designing reports, documents and interactive dashboards for building dashboards[*] Understand the concepts of data discovery and Desktop capabilities[*] Explore the best practices for Microstrategy system administration[*] Find and fix issues based on connections, environment or documents[*] Integrate third party ESRI map tools with MicroStrategy to create geo based reportsWho this book is forThis book is intended for BI, DWH, ETL developers, BI/DWH/Analytics managers, analysts, and business users who already have MicroStrategy in their organization and want to take it to the next level in order to increase performance and improve user experience. In addition, it helps the reader to migrate from MicroStrategy 9 to MicroStrategy 10 and to start using the new capabilities.

Perform advanced dashboard, visualization, and analytical techniques with Tableau Desktop, Tableau Prep, and Tableau ServerKey FeaturesUnique problem-solution approach to aid effective business decision-makingCreate interactive dashboards and implement powerful business intelligence solutionsIncludes best practices on using Tableau with modern cloud analytics servicesBook DescriptionTableau has been one of the most popular business intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. Tableau 2019.x Cookbook is full of useful recipes from industry experts, who will help you master Tableau skills and learn each aspect of Tableau's ecosystem.This book is enriched with features such as Tableau extracts, Tableau advanced calculations, geospatial analysis, and building dashboards. It will guide you with exciting data manipulation, storytelling, advanced filtering, expert visualization, and forecasting techniques using real-world examples. From basic functionalities of Tableau to complex deployment on Linux, you will cover it all. Moreover, you will learn advanced features of Tableau using R, Python, and various APIs. You will learn how to prepare data for analysis using the latest Tableau Prep. In the concluding chapters, you will learn how Tableau fits the modern world of analytics and works with modern data platforms such as Snowflake and Redshift. In addition, you will learn about the best practices of integrating Tableau with ETL using Matillion ETL.By the end of the book, you will be ready to tackle business intelligence challenges using Tableau's features.What you will learnUnderstand the basic and advanced skills of Tableau DesktopImplement best practices of visualization, dashboard, and storytellingLearn advanced analytics with the use of build in statisticsDeploy the multi-node server on Linux and WindowsUse Tableau with big data sources such as Hadoop, Athena, and SpectrumCover Tableau built-in functions for forecasting using R packagesCombine, shape, and clean data for analysis using Tableau PrepExtend Tableau's functionalities with REST API and R/PythonWho this book is forTableau 2019.x Cookbook is for data analysts, data engineers, BI developers, and users who are looking for quick solutions to common and not-so-common problems faced while using Tableau products. Put each recipe into practice by bringing the latest offerings of Tableau 2019.x to solve real-world analytics and business intelligence challenges. Some understanding of BI concepts and Tableau is required.

Solve real-world data problems and create data-driven workflows for easy data movement and processing at scale with Azure Data FactoryKey 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 DescriptionAzure 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 forThis 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.

Data Engineers guide to solve real-world problems encountered while building and transforming data pipelines using Azure's data integration toolKey FeaturesSolve real-world data problems and create data-driven workflows with ease using Azure Data FactoryBuild an ADF pipeline that operates on pre-built ML model and Azure AIGet up and running with Fabric Data Explorer and extend ADF with Logic Apps and Azure functionsBook DescriptionThis new edition of the Azure Data Factory book, fully updated to reflect ADS V2, will help you get up and running by showing you how to create and execute your first job in ADF. There are updated and new recipes throughout the book based on developments happening in Azure Synapse, Deployment with Azure DevOps, and Azure Purview. The current edition also runs you through Fabric Data Factory, Data Explorer, and some industry-grade best practices with specific chapters on each.You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines, as well as discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premises infrastructure with cloud-native tools to get relevant business insights. You'll familiarize yourself with the common errors that you may encounter while working with ADF and find out the solutions to them. 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 with its latest advancements as the main ETL and orchestration tool for your data warehouse projects.What you will learnBuild and Manage data pipelines with ease using the latest version of ADFConfigure, load data, and operate data flows with Azure SynapseGet up and running with Fabric Data FactoryWorking with Azure Data Factory and Azure PurviewCreate big data pipelines using Databricks and Delta tablesIntegrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure FunctionsLearn industry-grade best practices for using Azure Data FactoryWho this book is forThis book is for ETL developers, data warehouse and ETL architects, software professionals, and anyone else 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 a prerequisite.

Master end-to-end data engineering on Azure Databricks. From data ingestion and Delta Lake to CI/CD and real-time streaming, build secure, scalable, and performant data solutions with Spark, Unity Catalog, and ML tools.Key FeaturesBuild scalable data pipelines using Apache Spark and Delta LakeAutomate workflows and manage data governance with Unity CatalogLearn real-time processing and structured streaming with practical use casesImplement CI/CD, DevOps, and security for production-ready data solutionsExplore Databricks-native ML, AutoML, and Generative AI integrationBook Description"Data Engineering with Azure Databricks" is your essential guide to building scalable, secure, and high-performing data pipelines using the powerful Databricks platform on Azure. Designed for data engineers, architects, and developers, this book demystifies the complexities of Spark-based workloads, Delta Lake, Unity Catalog, and real-time data processing.Beginning with the foundational role of Azure Databricks in modern data engineering, you’ll explore how to set up robust environments, manage data ingestion with Auto Loader, optimize Spark performance, and orchestrate complex workflows using tools like Azure Data Factory and Airflow.The book offers deep dives into structured streaming, Delta Live Tables, and Delta Lake’s ACID features for data reliability and schema evolution. You’ll also learn how to manage security, compliance, and access controls using Unity Catalog, and gain insights into managing CI/CD pipelines with Azure DevOps and Terraform.With a special focus on machine learning and generative AI, the final chapters guide you in automating model workflows, leveraging MLflow, and fine-tuning large language models on Databricks. Whether you're building a modern data lakehouse or operationalizing analytics at scale, this book provides the tools and insights you need.What you will learnSet up a full-featured Azure Databricks environmentImplement batch and streaming ingestion using Auto LoaderOptimize Spark jobs with partitioning and cachingBuild real-time pipelines with structured streaming and DLTManage data governance using Unity CatalogOrchestrate production workflows with jobs and ADFApply CI/CD best practices with Azure DevOps and GitSecure data with RBAC, encryption, and compliance standardsUse MLflow and Feature Store for ML pipelinesBuild generative AI applications in DatabricksWho this book is forThis book is for data engineers, solution architects, cloud professionals, and software engineers seeking to build robust and scalable data pipelines using Azure Databricks. Whether you're migrating legacy systems, implementing a modern lakehouse architecture, or optimizing data workflows for performance, this guide will help you leverage the full power of Databricks on Azure. A basic understanding of Python, Spark, and cloud infrastructure is recommended.

Learn through hands-on exercises covering a variety of topics including data connections, analytics, and dashboards to effectively prepare for the Tableau Desktop Certified Associate examKey FeaturesPrepare for the Tableau Desktop Certified Associate exam with the help of tips and techniques shared by expertsImplement Tableau’s advanced analytical capabilities such as forecastingDelve into advanced Tableau features and explore best practices for building dashboardsBook DescriptionThe Tableau Desktop Certified Associate exam measures your knowledge of Tableau Desktop and your ability to work with data and data visualization techniques. This book will help you to become well-versed in Tableau software and use its business intelligence (BI) features to solve BI and analytics challenges.With the help of this book, you'll explore the authors' success stories and their experience with Tableau. You'll start by understanding the importance of Tableau certification and the different certification exams, along with covering the exam format, Tableau basics, and best practices for preparing data for analysis and visualization. The book builds on your knowledge of advanced Tableau topics such as table calculations for solving problems. You'll learn to effectively visualize geographic data using vector maps. Later, you'll discover the analytics capabilities of Tableau by learning how to use features such as forecasting. Finally, you'll understand how to build and customize dashboards, while ensuring they convey information effectively. Every chapter has examples and tests to reinforce your learning, along with mock tests in the last section.By the end of this book, you'll be able to efficiently prepare for the certification exam with the help of mock tests, detailed explanations, and expert advice from the authors.What you will learnApply Tableau best practices to analyze and visualize dataUse Tableau to visualize geographic data using vector mapsCreate charts to gain productive insights into data and make quality-driven decisionsImplement advanced analytics techniques to identify and forecast key valuesPrepare customized table calculations to compute specific valuesAnswer questions based on the Tableau Desktop Certified Associate exam with the help of mock testsWho this book is forThis Tableau certification book is for business analysts, BI professionals, and data analysts who want to become certified Tableau Desktop Associates and solve a range of data science and business intelligence problems using this example-packed guide. Some experience in Tableau Desktop is expected to get the most out of this book.