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    How To Gather And Use Data For Business Analysis
    How To Gather And Use Data For Business Analysis
    How To Gather And Use Data For Business Analysis
    Ebook58 pages44 minutes

    How To Gather And Use Data For Business Analysis

    By M.L. Humphrey

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    About this ebook

    These days the business world is full of talk about data science, big data, and how data analysis can transform your business.

     

    And it's absolutely true that collecting the right information, in the right way, analyzing that information, and then using it effectively to manage your business can give your business a competitive edge.

     

    But most businesses don't need to go so far as big data and data science. They just need to understand and implement some basic steps for gathering the right information about their business and using it effectively.

     

    Leveraging over twenty years of experience using data for business, M.L. Humphrey will walk you through what you need to know to help improve your bottom line today.

     

    So don't wait. Get started now.

     

    This title was previously published as Data Principles for Beginners.

    LanguageEnglish
    PublisherM.L. Humphrey
    Release dateApr 5, 2022
    ISBN9798201730826
    How To Gather And Use Data For Business Analysis
    Author

    M.L. Humphrey

    Hi there Sci Fi fans, my name is Maurice Humphrey. I am a Vermont native, husband, father, grandfather, well over 60, Navy veteran, retired IBM engineer, retired printer repairman, Graduated: Goddard Jr. College, VT Technical College, and Trinity College. Over the years I've written technical articles, taught technical classes, and presented at technical conventions. I've been reading science fiction for over 50 years now. First books were "Journey to the Centre of the Earth" by Jules Verne and "The Stars Are Ours" by Andre Norton. I've read and collected many great stories, and a considerable amount of junk ones as well. I'd say by now that I probably have a good idea of what I consider a good story.

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      Book preview

      How To Gather And Use Data For Business Analysis - M.L. Humphrey

      How to Gather and Use Data for Business Analysis

      ALSO BY M.L. HUMPHREY

      Listing of all books by M.L. Humphrey

      Regulatory Compliance Fundamentals

      AML Compliance Fundamentals

      Budgeting for Beginners

      Budgeting for Beginners

      Excel for Budgeting

      Excel for Beginners

      Word for Beginners

      Access for Beginners

      PowerPoint for Beginners

      HOW TO GATHER AND USE DATA FOR BUSINESS ANALYSIS

      M.L. HUMPHREY

      CONTENTS

      Introduction

      Understand Your Business

      Track Every Variable You Want to Analyze In a Usable Way

      Separate the Information You Want to Track Into Discrete Units

      Enter Once, Use Many Times

      Be Consistent Across Data Tables or Data Sources

      Use Categorical Variables Instead of Free Text Where Possible

      Use Dropdown Menus Where Feasible

      Consider Using an Other Option

      Keep Your Values Up To Date

      Take Care When Making Changes to Your Data

      Don't Change Your Raw Data

      Document Your Data Clean-Up and Analysis Steps

      Save Versions

      Test Your Results

      Make Assumptions Visible

      Know the Limitations of Your Programs

      Know the Difference Between a Report and Raw Data

      View Your Data From a Business Perspective

      Build In Checks and Balances Where You Can

      Activity-Based Costing

      Conclusion

      About the Author

      Copyright

      INTRODUCTION

      There's a lot of buzz these days around big data, data science, and data analysis. And for good reason. Because the more you understand about your business and your customers the more profitable your business can be.

      For example, say you have two products, widgets and whatchamacallits, but you don't track the product-level revenue or the product-level expenses. All you know is that last quarter you made $10,000 and you spent $8,000 and that you sold a lot more widgets than whatchamacallits.

      You might be tempted given that limited amount of information to think that you should abandon whatchamacallits and sell only widgets. But if you had detailed information about each product you would instead see that you made $6,000 selling whatchamacallits and $4,000 selling widgets and that your expense for selling those whatchamacallits was only $1,000 while your expense for selling widgets was $7,000.

      Put those product-level numbers together and you'd see that you made a profit of $5,000 on your whatchamacallit sales and lost $3,000 on your widget sales.

      Given those numbers, you'd want to abandon widget sales and focus on whatchamacallits. Or you'd want to fix the issue with why widgets are costing you more than they're making you.

      But do you see there why having good information about your business can be so valuable?

      Often we make decisions from the gut—I sure sell a lot of widgets, I must be good at that—instead of using factual information that maybe tells a different story. That's why collecting good data and using the data you have to the best effect is so important and crucial to success. That’s why all the buzz.

      But data science is a complicated field. There's a lot of that goes into doing it well and not everyone has the type of mind that can process data at those levels. I myself have dabbled in learning R programming and taken a few courses on big data and data science and while I found it interesting and challenging I realized that it wasn't really what I needed as a small business owner. I'm not trying to parse social trends by mining Twitter feeds, for example.

      I just want to know what product sells the best so I can make more of it.

      So what I'm going to cover for you in this book are some very basic principles around how to collect information, how to store that information, and how to use that information effectively. These principles are a good foundation for even highly complex analysis, but you don't

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