Learn how to automate processes, visualize your data, and improve productivity using Power Apps, Power Automate, Power BI, SharePoint, Forms, Teams, and more. This book will help you build complete solutions that often involve storing data in SharePoint, creating a front-end application in Power Apps or Forms, adding additional functionality with Power Automate, and effective reports and dashboards in Power BI. This new edition greatly expands the focus on Power Apps, Power BI, Power Automate, and Teams, along with SharePoint and Microsoft Forms. It starts with the basics of programming and shows how to build a simple email application in .NET, HTML/JavaScript, Power Apps on its own, and Power Apps and Power Automate in combination. It then covers how to connect Power Apps to SharePoint, create an approval process in Power Automate, visualize surveys in Power BI, and create your own survey solution with the combination of a number of Microsoft 365 tools. You’ll work with anextended example that shows how to use Power Apps and SharePoint together to create your own help ticketing system. This book offers a deep dive into Power BI, including working with JSON, XML, and Yes/No data, as well as visualizing learning data and using it to detect inconsistencies between Excel files. You’ll also see how to connect to Remedy and to the help system you will have created. Under author Jeffrey Rhodes’s guidance, you’ll delve into the Power Apps collection to learn how to avoid dreaded "delegation" issues with larger data sets. Back on applications, you will create a training class sign-up solution to only allow users to choose classes with available seats. Digging deeper into Teams, you’ll learn how to send chats, posts, and "adaptive cards" from Power Automate. Rounding things out, you’ll save Forms attachments to SharePoint with Power Automate, create your own "Employee Recognition" app with all of the Power Platform and Teams, add or edit weekly status reports, and learn how to create reservation and scoring applications. After reading the book, you will be able to build powerful applications using Power Apps, Power Automate, Power BI, SharePoint, Forms, and Teams. What You Will Learn Create productivity-enhancing applications with Power Apps, Power Automate, SharePoint, Forms, and/or Teams Transform and visualize data with Power BI to include custom columns, measures, and pivots Avoid delegation issues and tackle complicated Power Apps issues like complex columns, filtering, and ForAll loops Build scheduled or triggered Power Automate flows to schedule Teams Meetings, send emails, launch approvals, and much more Who This Book Is For Business and application developers.

An indispensable guide for statistical programmers in the pharmaceutical industry. Statistical programmers in the pharmaceutical industry need to create standardized clinical data using rules created and governed by the Clinical Data Interchange Standards Consortium (CDISC). This book introduces the basic concepts, pharmaceutical industry knowledge, and SAS programming practices that every programmer needs to know to comply with regulatory requirements. Step-by-step, you will learn how data should be structured at each stage of the process from annotating electronic Case Report Forms (eCRFs) and defining the relationship between SDTM and ADaM, to understanding how to generate a Define-XML file to transmit metadata. Filled with clear explanations and example code, this book focuses only on the essential information that entry-level programmers need to succeed.

This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools--useful whether you work with Windows, macOS, or Linux. You'll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you're comfortable processing data with Python or R, you'll learn how to greatly improve your data science workflow by leveraging the command line's power. This book is ideal for data scientists, analysts, engineers, system administrators, and researchers. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on text, CSV, HTML, XML, and JSON files Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow Create your own tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines Model data with dimensionality reduction, regression, and classification algorithms Leverage the command line from Python, Jupyter, R, RStudio, and Apache Spark

For decades researchers and programmers have used SAS to analyze, summarize, and report clinical trial data. Now Chris Holland and Jack Shostak have updated their popular Implementing CDISC Using SAS, the first comprehensive book on applying clinical research data and metadata to the Clinical Data Interchange Standards Consortium (CDISC) standards. Implementing CDISC Using SAS: An End-to-End Guide, Revised Second Edition, is an all-inclusive guide on how to implement and analyze the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM) data and prepare clinical trial data for regulatory submission. Updated to reflect the 2017 FDA mandate for adherence to CDISC standards, this new edition covers creating and using metadata, developing conversion specifications, implementing and validating SDTM and ADaM data, determining solutions for legacy data conversions, and preparing data for regulatory submission. The book covers products such as Base SAS, SAS Clinical Data Integration, and the SAS Clinical Standards Toolkit, as well as JMP Clinical. Topics included in this edition include an implementation of the Define-XML 2.0 standard, new SDTM domains, validation with Pinnacle 21 software, event narratives in JMP Clinical, STDM and ADAM metadata spreadsheets, and of course new versions of SAS and JMP software. The second edition was revised to add the latest C-Codes from the most recent release as well as update the make_define macro that accompanies this book in order to add the capability to handle C-Codes. The metadata spreadsheets were updated accordingly. Any manager or user of clinical trial data in this day and age is likely to benefit from knowing how to either put data into a CDISC standard or analyzing and finding data once it is in a CDISC format. If you are one such person--a data manager, clinical and/or statistical programmer, biostatistician, or even a clinician--then this book is for you.

Master the art of predictive modeling About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Familiarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naïve Bayes, decision trees, text mining and so on. We emphasize important concepts, such as the bias-variance trade-off and over-fitting, which are pervasive in predictive modeling Who This Book Is For If you work with data and want to become an expert in predictive analysis and modeling, then this Learning Path will serve you well. It is intended for budding and seasoned practitioners of predictive modeling alike. You should have basic knowledge of the use of R, although it’s not necessary to put this Learning Path to great use. What You Will Learn Get to know the basics of R’s syntax and major data structures Write functions, load data, and install packages Use different data sources in R and know how to interface with databases, and request and load JSON and XML Identify the challenges and apply your knowledge about data analysis in R to imperfect real-world data Predict the future with reasonably simple algorithms Understand key data visualization and predictive analytic skills using R Understand the language of models and the predictive modeling process In Detail Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. This Learning Path will provide you with all the steps you need to master the art of predictive modeling with R. We start with an introduction to data analysis with R, and then gradually you’ll get your feet wet with predictive modeling. You will get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. You will be able to solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. You will then perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. By the end of this Learning Path, you will have explored and tested the most popular modeling techniques in use on real-world data sets and mastered a diverse range of techniques in predictive analytics. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Data Analysis with R, Tony Fischetti Learning Predictive Analytics with R, Eric Mayor Mastering Predictive Analytics with R, Rui Miguel Forte Style and approach Learn data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach. This is a practical course, which analyzes compelling data about life, health, and death with the help of tutorials. It offers you a useful way of interpreting the data that’s specific to this course, but that can also be applied to any other data. This course is designed to be both a guide and a reference for moving beyond the basics of predictive modeling. Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the code file.

For decades researchers and programmers have used SAS to analyze, summarize, and report clinical trial data. Now Chris Holland and Jack Shostak have updated their popular Implementing CDISC Using SAS, the first comprehensive book on applying clinical research data and metadata to the Clinical Data Interchange Standards Consortium (CDISC) standards.

Implementing CDISC Using SAS: An End-to-End Guide, Second Edition, is an all-inclusive guide on how to implement and analyze the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM) data and prepare clinical trial data for regulatory submission. Updated to reflect the 2017 FDA mandate for adherence to CDISC standards, this new edition covers creating and using metadata, developing conversion specifications, implementing and validating SDTM and ADaM data, determining solutions for legacy data conversions, and preparing data for regulatory submission. The book covers products such as Base SAS, SAS Clinical Data Integration, and the SAS Clinical Standards Toolkit, as well as JMP Clinical. Topics included in this new edition include an implementation of the Define-XML 2.0 standard, new SDTM domains, validation with Pinnacle 21 software, event narratives in JMP Clinical, and of course new versions of SAS and JMP software.

Any manager or user of clinical trial data in this day and age is likely to benefit from knowing how to either put data into a CDISC standard or analyzing and finding data once it is in a CDISC format. If you are one such person--a data manager, clinical and/or statistical programmer, biostatistician, or even a clinician--then this book is for you.

Learning Pentaho CTools is a comprehensive guide to building sophisticated and custom analytics dashboards using the powerful capabilities of Pentaho CTools. This book walks you through the process of creating interactive dashboards, integrating data sources, and applying data visualization best practices. You'll quickly gain the expertise needed to create impactful dashboards with ease. What this Book will help me do Master installing and configuring CTools for Pentaho to jumpstart dashboard development. Harness diverse data sources and deliver data in formats like CSV, JSON, and XML for customized analytics. Design and implement dynamic, visually stunning dashboards using Community Dashboard Framework (CDF). Deploy and integrate plugins, leverage widgets, and manage dashboards effectively with version control. Enhance interactivity by customizing dashboard components, charts, and filters to suit unique requirements. Author(s) None Gaspar, an expert in Pentaho and its tools, has been a Senior Consultant at Pentaho, where he gained in-depth experience crafting analytics solutions. He brings to this book his teaching passion and field expertise, combining theoretical insights with practical applications. His approachable style ensures readers can follow technical concepts effectively. Who is it for? This book is ideal for developers who are looking to enhance their understanding of Pentaho's CTools portfolio to build advanced dashboards. A working knowledge of JavaScript and CSS will enable readers to get the most out of this guide. Whether you aim to extend your analytics capabilities or learn the tools from scratch, this book bridges the gap between learning and application.

A hands on guide to web scraping and text mining for both beginners and experienced users of R Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL. Provides basic techniques to query web documents and data sets (XPath and regular expressions). An extensive set of exercises are presented to guide the reader through each technique. Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management. Case studies are featured throughout along with examples for each technique presented. R code and solutions to exercises featured in the book are provided on a supporting website.

This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data. To get you started—whether you’re on Windows, OS X, or Linux—author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools. Discover why the command line is an agile, scalable, and extensible technology. Even if you’re already comfortable processing data with, say, Python or R, you’ll greatly improve your data science workflow by also leveraging the power of the command line. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on plain text, CSV, HTML/XML, and JSON Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow using Drake Create reusable tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines using GNU Parallel Model data with dimensionality reduction, clustering, regression, and classification algorithms

"Getting Started with Beautiful Soup" is your practical guide to website scraping using Python. It teaches you how to use Beautiful Soup and the urllib2 module to extract data from websites efficiently and effectively. Through hands-on examples and clear explanations, you'll gain the skills to navigate, search, and modify HTML content. What this Book will help me do Navigate and scrape web pages using the Beautiful Soup Python library. Understand and implement the urllib2 module to access web content programmatically. Search and analyze HTML structures efficiently to extract the needed data. Modify and format extracted HTML and XML content effectively. Handle encoding and manage output formats for diverse scraping requirements. Author(s) Vineeth G. Nair is an experienced Python developer with a strong focus on web technologies, data extraction, and automation. His expertise in Python's Beautiful Soup library has helped countless learners and professionals tackle the challenges of web scraping. Vineeth combines a methodical approach to teaching with practical examples, making complex concepts accessible and actionable. Who is it for? This book is ideal for Python enthusiasts, data analysts, and budding developers looking to explore web scraping. Whether you're a beginner or have some programming experience, this book will guide you through the fundamental concepts of extracting web data. If you're aiming to delve into practical, real-world implementations of web scraping, this is the book for you.

PROC REPORT by Example: Techniques for Building Professional Reports Using SAS provides real-world examples using PROC REPORT to create a wide variety of professional reports. Written from the point of view of the programmer who produces the reports, this book explains and illustrates creative techniques used to achieve the desired results.

Each chapter focuses on a different concrete example, shows an image of the final report, and then takes you through the process of creating that report. You will be able to break each report down to find out how it was produced, including any data manipulation you have to do.

The book clarifies solutions to common, everyday programming challenges and typical daily tasks that programmers encounter. For example: obtaining desired report formats using style templates supplied by SAS and PROC TEMPLATE, PROC REPORT STYLE options, and COMPUTE block features employing different usage options (DISPLAY, ORDER, GROUP, ANALYSIS, COMPUTED) to create a variety of detail and summary reports using BREAK statements and COMPUTE blocks to summarize and report key findings producing reports in various Output Delivery System (ODS) destinations including RTF, PDF, XML, TAGSETS.RTF embedding images in a report and combining graphical and tabular data with SAS 9.2 and beyond

Applicable to SAS users from all disciplines, the real-life scenarios will help elevate your reporting skills learned from other books to the next level.

With PROC REPORT by Example: Techniques for Building Professional Reports Using SAS, what seemed complex will become a matter of practice.

This book is part of the SAS Press program.

Mondrian in Action teaches business users and developers how to use Mondrian and related tools for strategic business analysis. You'll learn how to design and populate a data warehouse and present the data via a multidimensional model. You'll follow examples showing how to create a Mondrian schema and then expand it to add basic security based on the users' roles. About the Technology Mondrian is an open source, lightning-fast data analysis engine designed to help you explore your business data and perform speed-of-thought analysis. Mondrian can be integrated into a wide variety of business analysis applications and learning it requires no specialized technical knowledge. About the Book Mondrian in Action teaches you to use Mondrian for strategic business analysis. In it, you'll learn how to organize and present data in a multidimensional manner. You'll follow apt and thoroughly explained examples showing how to create a Mondrian schema and then expand it to add basic security based on users' roles. Developers will discover how to integrate Mondrian using its olap4j Java API and web service calls via XML for Analysis. What's Inside Mondrian from the ground up -- no experience required A primer on business analytics Using Mondrian with a variety of leading applications Optimizing and restricting business data for fast, secure analysis About the Reader Written for developers building data analysis solutions. Appropriate for tech-savvy business users and DBAs needing to query and report on data. About the Authors William D. Back is an Enterprise Architect and Director of Pentaho Services. Nicholas Goodman is a Business Intelligence pro who has authored training courses on OLAP and Mondrian. Julian Hyde founded Mondrian and is the project's lead developer. Quotes A wonderful introduction to Business Intelligence and Analytics. - Lorenzo De Leon, Authentify, Inc. A great overview of the Mondrian engine that guided me through all the technical details. - Alexander Helf, veenion GmbH A significant complement to the online documentation, and an excellent introduction to how to think about designing a data warehouse. - Mark Newman, Heads Up Analytics Comprehensive ... highly recommended. - Najib Coutya, IMD Group

This cookbook is a comprehensive guide to mastering IBM Cognos 10 Report Studio, enabling users to become proficient in developing professional-grade reports. Through practical recipes, you will learn how to harness the full potential of Report Studio, mastering both fundamental and advanced features for real-world application. What this Book will help me do Efficiently organize and process data using advanced sorting and filtering techniques. Create visually engaging and functional reports, including dynamic drill-through links and enhanced formatting options. Master the use of conditional formatting, cascaded prompts, and master-detailed queries in your reports. Enhance reports with Active Reports, direct XML editing, and by integrating JavaScript and HTML elements. Adopt industry best practices for report development, including version control and regression testing. Author(s) The author of this cookbook is an experienced IBM Cognos consultant with years of experience in developing business intelligence solutions and creating comprehensive reports. They focus on combining technical expertise with practical examples, presenting information in an approachable and user-friendly manner. Who is it for? This book is ideal for Business Intelligence Developers with a working knowledge of IBM Cognos 10 who seek to enhance their report-building skills. It also serves Business Analysts or Power Users familiar with basic report authoring who aim to explore advanced features. Prior knowledge of IBM Cognos 10 architecture and basic Report Studio functionalities is assumed.

SAS Server Pages have been used by SAS developers as a way of creating custom user interfaces for Web-based applications. This enhanced book offers information on how to create SAS Server Pages using the SAS 9.3 experimental procedure PROC STREAM, providing users with a foundation technology that greatly expands the capabilities of SAS for dynamic and rich content generation. By combining PROC STREAM and the Macro facility, SAS can now more easily generate any type of markup or text-based content such as HTML, XML, and CSV.

Exclusively available in electronic format, this book provides more extensive and flexible ways to develop applications using video examples of a wide range of PROC STREAM and SAS Server Pages techniques, including both Web applications and Base SAS implementations. Users can see results immediately and can access additional content and information online through embedded links. It also offers basic how-to documentation on PROC STREAM and an overview of a Portal Reporting Framework that illustrates creating custom user interfaces for stored processes within the SAS Portal.

Ideal for SAS programmers who have some knowledge of the Macro facility as well as BI users, SAS Server Pages: Generating Dynamic Content removes the difficulties associated with HTML-based content creation while providing a resource on using PROC STREAM in a dynamic, enhanced format.

Building on the unique features that made the first edition a bestseller, this second edition includes additional solved problems and web access to the large collection of MATLAB scripts that are highlighted throughout the text. The book offers expanded coverage of audio engineering, transducers, and sensor networking technology. It also includes new chapters on digital audio processing, as well as acoustics and vibrations transducers. The text addresses the use of meta-data architectures using XML and agent-based automated data mining and control. The numerous algorithms presented can be applied locally or network-based to solve complex detection problems.

How do you use R to import, manage, visualize, and analyze real-world data? With this short, hands-on tutorial, you learn how to collect online data, massage it into a reasonable form, and work with it using R facilities to interact with web servers, parse HTML and XML, and more. Rather than use canned sample data, you'll plot and analyze current home foreclosure auctions in Philadelphia. This practical mashup exercise shows you how to access spatial data in several formats locally and over the Web to produce a map of home foreclosures. It's an excellent way to explore how the R environment works with R packages and performs statistical analysis. Parse messy data from public foreclosure auction postings Plot the data using R's PBSmapping package Import US Census data to add context to foreclosure data Use R's lattice and latticeExtra packages for data visualization Create multidimensional correlation graphs with the pairs() scatterplot matrix package

More than seven million people have downloaded BIRT (Business Intelligence and Reporting Tools) from the Eclipse web site, and more than one million developers are estimated to be using BIRT. Built on the open source Eclipse platform, BIRT is a powerful report development system that provides an end-to-end solution–from creating and deploying reports to integrating report capabilities in enterprise applications. The first in a two-book series about this exciting technology, is the authoritative guide to using BIRT Report Designer, the graphical tool that enables users of all levels to build reports, from simple to complex, without programming. BIRT: A Field Guide to Reporting, Third Edition, This book is an essential resource for users who want to create presentation-quality reports quickly. The extensive examples, step-by-step instructions, and abundant illustrations help new users develop report design skills. Power users can find the information they need to make the most of the product’s rich set of features to build sophisticated and compelling reports. Readers of this book learn how to Design effective corporate reports that convey complex business information using images, charts, tables, and cross tabs Build reports using data from multiple sources, including databases, spreadsheets, web services, and XML documents Enliven reports with interactive features, such as hyperlinks, tooltips, and highlighting Create reports using a consistent style, and, drawing on templates and libraries of reusable elements, collaborate with other report designers Localize reports for an international audience The third edition, newly revised for BIRT 2.6, adds updated examples, contains close to 1,000 new and replacement screenshots, and covers all the new and improved product features, including Result-set sharing to create dashboard-style reports Data collation conforming to local conventions Using cube data in charts, new chart types, and functionality Displaying bidirectional text, used in right-to-left languages Numerous enhancements to cross tabs, page management, and report layout

The "IBM Cognos 8 Report Studio Cookbook" by Abhishek Sanghani provides over 80 hands-on recipes to enhance your proficiency in creating business reports using Cognos 8 Report Studio. From mastering basic techniques to leveraging advanced features, this book is your guide to developing reports that meet real-world business demands. What this Book will help me do Understand and utilize advanced techniques for sorting, filtering, and aggregating data in reports. Implement features like conditional formatting, cascaded prompts, and master-detail queries to enhance report functionality. Create dynamic, user-friendly business reports tailored to specific requirements. Make use of XML specifications to customize reports beyond the capabilities of the default tools. Adopt best practices in report development such as version control and regression testing. Author(s) Abhishek Sanghani is an experienced Business Intelligence professional specializing in IBM Cognos and data analytics. With practical knowledge from implementing solutions for various industries, he brings a wealth of insight into creating powerful business reports. Abhishek's approachable writing makes advanced Report Studio concepts accessible to readers. Who is it for? This book is ideally suited for Business Intelligence or MIS developers working with Cognos Report Studio, seeking advanced guidance for creating reports. Business analysts and power users wanting to extend beyond basic report authoring will also benefit greatly. The book assumes a functional understanding of Cognos Studio and familiarity with its ecosystem.

This article demonstrates how the realworld data is imported, managed, visualized, and analyzed within the R statistical framework. Presented as a spatial mashup, this tutorial introduces the user to R packages, R syntax, and data structures. The user will learn how the R environment works with R packages as well as its own capabilities in statistical analysis. We will be accessing spatial data in several formats-html, xml, shapefiles, and text-locally and over the web to produce a map of home foreclosure auctions and perform statistical analysis on these events.

Written by a member of the R Development Core Team, this resource provides important information on how to work with research data. It contains a collection of diverse, computer-related topics, connecting them through numerous, real-world case studies. The author describes open source technologies and open standards and devotes separate chapters to each computer language, including HTML, XML, SQL, and R. Explanatory diagrams aid in understanding important concepts, helping readers perform research tasks with ease. In addition, the author's website includes a suite of exercises as well as the code and data sets used in the case studies.