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Author: Luca Zavarella
Publisher: Packt Publishing Ltd
ISBN: 1801076677
Category : Computers
Languages : en
Pages : 559
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Book Description
Perform more advanced analysis and manipulation of your data beyond what Power BI can do to unlock valuable insights using Python and R Key FeaturesGet the most out of Python and R with Power BI by implementing non-trivial codeLeverage the toolset of Python and R chunks to inject scripts into your Power BI dashboardsImplement new techniques for ingesting, enriching, and visualizing data with Python and R in Power BIBook Description Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages. You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model. By the end of this book, you'll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R. What you will learnDiscover best practices for using Python and R in Power BI productsUse Python and R to perform complex data manipulations in Power BIApply data anonymization and data pseudonymization in Power BILog data and load large datasets in Power BI using Python and REnrich your Power BI dashboards using external APIs and machine learning modelsExtract insights from your data using linear optimization and other algorithmsHandle outliers and missing values for multivariate and time-series dataCreate any visualization, as complex as you want, using R scriptsWho this book is for This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.
Author: Luca Zavarella
Publisher: Packt Publishing Ltd
ISBN: 1801076677
Category : Computers
Languages : en
Pages : 559
Get Book Here
Book Description
Perform more advanced analysis and manipulation of your data beyond what Power BI can do to unlock valuable insights using Python and R Key FeaturesGet the most out of Python and R with Power BI by implementing non-trivial codeLeverage the toolset of Python and R chunks to inject scripts into your Power BI dashboardsImplement new techniques for ingesting, enriching, and visualizing data with Python and R in Power BIBook Description Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages. You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model. By the end of this book, you'll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R. What you will learnDiscover best practices for using Python and R in Power BI productsUse Python and R to perform complex data manipulations in Power BIApply data anonymization and data pseudonymization in Power BILog data and load large datasets in Power BI using Python and REnrich your Power BI dashboards using external APIs and machine learning modelsExtract insights from your data using linear optimization and other algorithmsHandle outliers and missing values for multivariate and time-series dataCreate any visualization, as complex as you want, using R scriptsWho this book is for This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.
Author: Ryan Wade
Publisher: Apress
ISBN: 9781484258286
Category : Computers
Languages : en
Pages : 330
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Book Description
This easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard to do, if not impossible, using native Power BI tools without Power BI Premium capacity. For example, you will learn to score Power BI data using custom data science models, including powerful models from Microsoft Cognitive Services. The R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support. If you are a BI developer, business analyst, data analyst, or a data scientist who wants to push Power BI and transform it from being just a business intelligence tool into an advanced data analytics tool, then this is the book to help you to do that. What You Will Learn Create advanced data visualizations through R using the ggplot2 package Ingest data using R and Python to overcome the limitations of Power Query Apply machine learning models to your data using R and Python Incorporate advanced AI in Power BI via Microsoft Cognitive Services, IBM Watson, and pre-trained models in SQL Server Machine Learning Services Perform string manipulations not otherwise possible in Power BI using R and Python Who This Book Is For Power users, data analysts, and data scientists who want to go beyond Power BI’s built-in functionality to create advanced visualizations, transform data in ways not otherwise supported, and automate data ingestion from sources such as SQL Server and Excel in a more succinct way
Author: David Taieb
Publisher: Packt Publishing Ltd
ISBN: 1789958199
Category : Computers
Languages : en
Pages : 491
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Book Description
Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis. Key FeaturesBridge your data analysis with the power of programming, complex algorithms, and AIUse Python and its extensive libraries to power your way to new levels of data insightWork with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time seriesExplore this modern approach across with key industry case studies and hands-on projectsBook Description Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence. What you will learnA new toolset that has been carefully crafted to meet for your data analysis challengesFull and detailed case studies of the toolset across several of today’s key industry contextsBecome super productive with a new toolset across Python and Jupyter NotebookLook into the future of data science and which directions to develop your skills nextWho this book is for This book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.
Author: Bhavik Merchant
Publisher: Packt Publishing Ltd
ISBN: 180107139X
Category : Computers
Languages : en
Pages : 312
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Book Description
Supercharge performance analytics and create repeatable patterns to ensure you get the best performance and scalability from your analytics solutions with Power BI Key Features Learn how to build performant data models and apply Row-Level Security Identify and fix performance issues in reports, DAX, and datasets using DAX Studio/VertiPaq Analyzer Use a formal process to manage performance, from setting targets to monitoring and remediating issues Book DescriptionThis book comprehensively covers every layer of Power BI, from the report canvas to data modeling, transformations, storage, and architecture. Developers and architects working with any area of Power BI will be able to put their knowledge to work with this practical guide to design and implement at every stage of the analytics solution development process. This book is not only a unique collection of best practices and tips, but also provides you with a hands-on approach to identifying and fixing common performance issues. Complete with explanations of essential concepts and practical examples, you’ll learn about common design choices that affect performance and consume more resources and how to avoid these problems. You’ll grasp the general architectural issues and settings that broadly affect most solutions. As you progress, you’ll walk through each layer of a typical Power BI solution, learning how to ensure your designs can handle scale while not sacrificing usability. You’ll focus on the data layer and then work your way up to report design. We will also cover Power BI Premium and load testing. By the end of this Power BI book, you’ll be able to confidently maintain well-performing Power BI solutions with reduced effort and know how to use freely available tools and a systematic process to monitor and diagnose performance problems.What you will learn Understand how to set realistic performance targets and address performance proactively Understand how architectural options and configuration affect performance Build efficient Power BI reports and data transformations Explore best practices for data modeling, DAX, and large datasets Understand the inner workings of Power BI Premium Explore options for extreme scale with Azure services Understand how to use tools that help identify and fix performance issues Who this book is for Data analysts, BI developers, and data professionals who have learnt the basics of Power BI and now want to understand how to build advanced analytics solutions will find this business intelligence book useful. Familiarity with the major components of Power BI and a beginner-level understanding of their purpose and use cases are required.
Author: Mary-Jo Diepeveen
Publisher: Packt Publishing Ltd
ISBN: 1801816255
Category : Computers
Languages : en
Pages : 348
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Book Description
Learn how to create your own AI model and consume it in your Power BI reports to gain better insights from your data Key FeaturesLearn how to gain better insights from your data by applying different AI techniques within Power BISave time by creating machine learning models independently and integrating them within your BI reportsUnderstand how to combine Cognitive Services and Azure Machine Learning together with Power BIBook Description The artificial intelligence (AI) capabilities in Power BI enable organizations to quickly and easily gain more intelligent insights from unstructured and structured data. This book will teach you how to make use of the many AI features available today in Power BI to quickly and easily enrich your data and gain better insights into patterns that can be found in your data. You'll begin by understanding the benefits of AI and how it can be used in Power BI. Next, you'll focus on exploring and preparing your data for building AI projects and then progress to using prominent AI features already available in Power BI, such as forecasting, anomaly detection, and Q&A. Later chapters will show you how to apply text analytics and computer vision within Power BI reports. This will help you create your own Q&A functionality in Power BI, which allows you to ask FAQs from another knowledge base and then integrate it with PowerApps. Toward the concluding chapters, you'll be able to create and deploy AutoML models trained in Azure ML and consume them in Power Query Editor. After your models have been trained, you'll work through principles such as privacy, fairness, and transparency to use AI responsibly. By the end of this book, you'll have learned when and how to enrich your data with AI using the out-of-the-box AI capabilities in Power BI. What you will learnApply techniques to mitigate bias and handle outliers in your dataPrepare time series data for forecasting in Power BIPrepare and shape your data for anomaly detectionUse text analytics in Power Query EditorIntegrate QnA Maker with PowerApps and create an appTrain your own models and identify the best one with AutoMLIntegrate an Azure ML workspace with Power BI and use endpoints to generate predictionsWho this book is for This artificial intelligence BI book is for data analysts and BI developers who want to explore advanced analytics or artificial intelligence possibilities with their data. Prior knowledge of Power BI will help you get the most out of this book.
Author: Gregory Deckler
Publisher: Packt Publishing Ltd
ISBN: 1835086160
Category : Computers
Languages : en
Pages : 759
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Book Description
Learn how to use the Power Query M formula language and its functions effectively for better data modeling and impactful business intelligence reports. Purchase of the print or Kindle book includes a free PDF eBook Key Features Get comprehensive coverage of fundamental and advanced Power Query concepts Gain hands-on experience with practical examples based on real-world problems Delve into the intricacies of Power Query M language for enhanced data manipulation Book DescriptionData transformation is a critical step in building data models and business intelligence reports. Power Query is an invaluable tool for anyone who wants to master data transformation, and this book will equip you with the knowledge and skills to make the most of it. The Definitive Guide to Power Query (M) will help you build a solid foundation in the Power Query M language. As you progress through the chapters, you'll learn how to use that knowledge to implement advanced concepts and data transformations. This will set the stage for an uncompromisingly thorough exploration of the Power Query M Language. You'll also get to grips with optimizing performance, handling errors, and implementing efficient data processing techniques. As this is a hands-on guide, the practical examples in the chapters will help you gain the skills to apply Power Query to real-world problems and improve your data analysis capabilities. By the end of this book, you will be able to leverage all of Power Query's remarkable capabilities for data transformation.What you will learn Gain a strong understanding of Power Query fundamentals Master various functions within Power Query to perform complex data operations Acquire knowledge about values, types, and control structures in Power Query Develop proficiency in error handling techniques Learn performance optimization strategies for Power Query Apply what you’ve learned to real-world scenarios, including common troublesome patterns Who this book is for This book is for business analysts, business intelligence professionals, and power business users working with data who want to add Power Query mastery to their resume. This book will be beneficial for anyone who wants to automate their process of data cleaning and save huge amount of time. Having some basic experience in Power Query is recommended.
Author: Rick J. Scavetta
Publisher: "O'Reilly Media, Inc."
ISBN: 1492093378
Category : Computers
Languages : en
Pages : 199
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Book Description
Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a case study that demonstrates ways to use these languages together
Author: Mark Tossell
Publisher: Packt Publishing Ltd
ISBN: 1801070245
Category : Computers
Languages : en
Pages : 368
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Book Description
Leverage CRM Analytics to generate valuable business insights and solve business problems efficiently Key FeaturesExtract, combine, transform, and visualize your data to derive business insights using CRM AnalyticsGain hands-on experience as you walk through practical dashboard use cases in CRM AnalyticsLearn how to build best-in-class dashboards from a CRM Analytics thought leaderBook Description CRM Analytics, formerly known as Tableau CRM and Einstein Analytics, is a powerful and versatile data analytics platform that enables organizations to extract, combine, transform, and visualize their data to create valuable business insights. Creating Actionable Insights Using CRM Analytics provides a hands-on approach to CRM Analytics implementation and associated methodologies that will have you up and running and productive in no time. The book provides you with detailed explanations of essential concepts to help you to gain confidence and become competent in using the CRM Analytics platform for data extraction, combination, transformation, visualization, and action. As you make progress, you'll understand what CRM Analytics is and where it provides business value. You'll also learn how to bring your data together in CRM Analytics, build datasets and lenses for data analysis, create effective analytics dashboards for visualization and consumption by end users, and build dashboard actions that take the user from data to insight to action with ease. By the end of this book, you'll be able to solve business problems using CRM Analytics and design, build, test, and deploy analytics dashboards efficiently. What you will learnImplement and configure CRM Analytics from scratchBuild your first CRM Analytics app and embed your CRM Analytics dashboards in Salesforce to enhance user adoptionConnect Salesforce and external data with CRM Analytics and create datasetsCreate a data recipe and get familiar with the recipe UIBuild a custom dashboard in CRM Analytics using the dashboard editorUse lenses to create a CRM Analytics dashboardConfigure and implement data security and governanceBuild configured record actions to automate data directly in SalesforceWho this book is for This book is for data analysts, business analysts, BI professionals, and Salesforce users who want to explore CRM Analytics' capabilities and features. Basic knowledge of Salesforce and data analytics is assumed to get the most out of this book.
Author: Greg Deckler
Publisher: Packt Publishing Ltd
ISBN: 1835464661
Category : Computers
Languages : en
Pages : 599
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Book Description
Now in color, this edition helps you unlock the full potential of Power BI with new recipes and comprehensive techniques on advanced data tools and AI Key Features Dive into Microsoft Data Fabric for deeper insights and robust data strategies Implement Hybrid tables, create comprehensive scorecards, and establish shared cloud connections effortlessly Uncover new and updated data visualization tools that turn complex data into clear, actionable charts and reports Purchase of the print or Kindle book includes a free eBook in PDF format Book DescriptionSince its first edition the Power BI Cookbook has been a best-selling resource for BI developers and data analysts to produce impactful, quality BI solutions. This new and updated edition retains the rigorous details and concepts readers of prior editions have enjoyed while also demonstrating powerful new capabilities and updated guidance aligned to the current state of the platform. In this book, with step-by-step instructions, you will learn to navigate the complexities of data integration and visualization in Power BI. From creating robust data models to implementing sophisticated reporting techniques, this Power BI book empowers you to make informed decisions based on actionable insights. It also introduces you to new capabilities such as Hybrid tables and scorecards, enhancing your ability to communicate and analyze business performance. It also expands and improvises on the core of the previous edition like parameterizing Power BI solutions, authoring reports, data intelligence, and integrating advanced analytics. This edition not only updates you on the latest features but also prepares you for future innovations with a preview of upcoming AI enhancements in Power BI. Whether you're refining your skills or aspiring to become an expert, this book is an invaluable resource for leveraging Power BI to its fullest potentialWhat you will learn Analyze and integrate business data using Microsoft Data Fabric Create impactful visualizations and manage Hybrid tables Develop shared cloud connections and advanced scorecards Enhance report accuracy and dynamics using real-time data processing Implement efficient data governance and security measures within Power BI Who this book is for This book is designed for data analysts, business intelligence professionals, and anyone involved in data processing or analytics who seeks to enhance their skills with Power BI’s latest features and prepare for future advancements in the field
Author: Bhisham C. Gupta
Publisher: John Wiley & Sons
ISBN: 1119671728
Category : Technology & Engineering
Languages : en
Pages : 404
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Book Description
STATISTICAL QUALITY CONTROL Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectors This book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept. Statistical Quality Control: Using MINITAB, R, JMP and Python begins with a brief discussion of the different types of data encountered in various fields of statistical applications and introduces graphical and numerical tools needed to conduct preliminary analysis of the data. It then discusses the basic concept of statistical quality control (SQC) and Six Sigma Methodology and examines the different types of sampling methods encountered when sampling schemes are used to study certain populations. The book also covers Phase 1 Control Charts for variables and attributes; Phase II Control Charts to detect small shifts; the various types of Process Capability Indices (CPI); certain aspects of Measurement System Analysis (MSA); various aspects of PRE-control; and more. This helpful guide also Focuses on the learning and understanding of statistical quality control for second and third year undergraduates and practitioners in the field Discusses aspects of Six Sigma Methodology Teaches readers to use MINITAB, R, JMP and Python to create and analyze charts Requires no previous knowledge of statistical theory Is supplemented by an instructor-only book companion site featuring data sets and a solutions manual to all problems, as well as a student book companion site that includes data sets and a solutions manual to all odd-numbered problems Statistical Quality Control: Using MINITAB, R, JMP and Python is an excellent book for students studying engineering, statistics, management studies, and other related fields and who are interested in learning various techniques of statistical quality control. It also serves as a desk reference for practitioners who work to improve quality in various sectors, such as manufacturing, service, transportation, medical, oil, and financial institutions. It‘s also useful for those who use Six Sigma techniques to improve the quality of products in such areas.
