This Straight to the Point guide provides an introduction to data cleansing, which also goes by names such as data munging and data wrangling. Whatever the name, it basically means doing what needs to be done to make data useful and trustworthy. Data cleansing can include the following tasks:Deleting unnecessary headersDeleting summary rowsFilling in gapsFlattening a reportMerging and appending data from multiple sourcesPulling data from source X to complete data in source YSplitting names from addressesIdentifying and deleting duplicate recordsConverting units of measurement in multiple sources
Author Oz Du Soleil's area of frustration with Excel is cleaning data. From his earliest days with Excel, he has found himself constantly needing to fix names that are ALLCAPS, peel addresses away from phone numbers, and fixing all the many other things that prevent data from being useful. In this intro to Power Query, Oz shows you five core techniques in Excel Power Query: Splitting data, Filling blanks, Joining data sets, grouping and summarizing, and adding columns using Column From Examples.
Master Excel data analysis with this hands-on guide. Learn efficient techniques, advanced functions, and best practices for real-world scenarios. Key Features Hands-on techniques for efficient Excel data analysis Advanced functions and best practices for real-world scenarios Step-by-step guidance on complex tasks like data validation and dynamic arrays Book DescriptionUnlock Microsoft Excel's hidden potential with this dynamic guide designed for data professionals and enthusiasts. You'll start by reviewing Excel basics before advancing to powerful tools like Excel Tables, Pivot Tables, and Power Query. Each chapter enhances your ability to analyze and visualize data efficiently, from complex lookups and dynamic arrays to essential data validation techniques that ensure accuracy and integrity in your spreadsheets. As you progress, you'll learn how to protect your work with advanced sheet protection methods and collaboration tools for seamless teamwork. The book also covers sophisticated functions like INDIRECT, OFFSET, and LET, preparing you to tackle complex data challenges. Additionally, you'll receive critical advice on avoiding the pitfalls of machine learning-driven features and maintaining clean, organized data. By the end of the guide, you'll have mastered Excel's advanced capabilities, empowering you to streamline workflows, optimize data processes, and make confident, data-driven decisions. This guide is your comprehensive resource for transforming your approach to data analysis with Excel.What you will learn Master Excel tables and dynamic spreadsheets Use VLOOKUP and XLOOKUP effectively Create and manipulate PivotTables Clean and validate data with Excel tools Apply conditional formatting and de-duping techniques Implement data models and relationships in Excel Who this book is for This book is ideal for data analysts, business professionals, and Excel users who need to enhance their data analysis skills. Readers should have a basic understanding of Excel and be familiar with its interface. No advanced Excel knowledge is required, but a willingness to learn and apply new techniques is essential.
Conquer Microsoft Excel 2019–from the inside out! Dive into Microsoft Excel 2019–and really put your spreadsheet expertise to work. This supremely organized reference packs hundreds of timesaving solutions, tips, and workarounds–all you need to make the most of Excel’s most powerful tools for analyzing data and making better decisions. Renowned Excel expert Bill Jelen offers a complete tour of Excel 2019 and Excel in Office 365, from efficient interface customizations to advanced analysis, visualizations, and dashboards. Discover how experts tackle today’s key tasks–and challenge yourself to new levels of mastery. Enter formulas more efficiently, and fully control operators and dates Master the most widely-used functions in Excel Integrate external data from the web and other sources Easily transform complex datasets with Power Query Quickly summarize millions of records with Pivot Tables Perform ad hoc analyses with slicers and other filters Create advanced data mashups with Power Pivot Solve complex problems with What-If, Scenario Manager, Goal Seek, and Solver Automate repetitive tasks by editing recorded VBA code Demystify data with conditional formatting and other visualization techniques Use the newest maps, charts, and data types in Excel Show geographical changes over time with animated 3D maps Use dynamic array functions: SORT, FILTER, UNIQUE, SORTBY and SEQUENCE Find insights using Excel’s new artificial intelligence Collaborate via Excel 2019’s breakthrough CoAuthoring tools Publish Power BI Desktop dashboards based on Excel data
Data use in the library has specific characteristics and common problems. Data Clean-up and Management addresses these, and provides methods to clean up frequently-occurring data problems using readily-available applications. The authors highlight the importance and methods of data analysis and presentation, and offer guidelines and recommendations for a data quality policy. The book gives step-by-step how-to directions for common dirty data issues. - Focused towards libraries and practicing librarians - Deals with practical, real-life issues and addresses common problems that all libraries face - Offers cradle-to-grave treatment for preparing and using data, including download, clean-up, management, analysis and presentation
Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University
New for Office 365 customers, one single formula sitting in one single cell can return many results. Those extra results will spill into adjacent cells. This is a major change to the calculation engine in Excel. This book covers the new functions added for Dynamic Arrays: SORT, SORTBY, FILTER, UNIQUE, SEQUENCE and RANDARRAY. It shows how Dynamic Arrays make the new XLOOKUP even more powerful. Dynamic arrays make every Excel calculation function more powerful. Pass a SEQUENCE to another function and Excel will Lift the function to return many results. Learn how to use the new # and @ operators in your formulas. After fifteen months of preview, the Dynamic Arrays are reaching general availability. Learn how the FastExcel SpeedTools add-in offers much-needed improvements, such as TOTALS, SLICES, VSTACK and UNPIVOT. Join in lobbying the Excel team to incorporate these improvements.
Power Query is one component of the Power BI (Business Intelligence) product from Microsoft, and "M" is the name of the programming language created by it. As more business intelligence pros begin using Power Pivot, they find that they do not have the Excel skills to clean the data in Excel; Power Query solves this problem. This book shows how to use the Power Query tool to get difficult data sets into both Excel and Power Pivot, and is solely devoted to Power Query dashboarding and reporting.
Many researchers jump straight from data collection to data analysis without realizing how analyses and hypothesis tests can go profoundly wrong without clean data. This book provides a clear, step-by-step process of examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of Best Practices in Quantitative Methods (SAGE, 2008) provides easily-implemented suggestions that are research-based and will motivate change in practice by empirically demonstrating, for each topic, the benefits of following best practices and the potential consequences of not following these guidelines. If your goal is to do the best research you can do, draw conclusions that are most likely to be accurate representations of the population(s) you wish to speak about, and report results that are most likely to be replicated by other researchers, then this basic guidebook will be indispensible.
