Tài liệu Microsoft Access 2007 Data Analysis P1 pdf

Append Queries 68Using the Query Design Grid to Create Your Crosstab Finding and Removing Duplicate Records 96 Augmenting Field Values with Your Own Text 105 Removing Leading and Traili

Michael Alexander

Data Analysis

Microsoft ® Access ™ 2007

Data Analysis

Michael Alexander

Data Analysis

Microsoft ® Access™ 2007 Data Analysis

Published by

Wiley Publishing, Inc.

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Copyright © 2007 by Wiley Publishing, Inc., Indianapolis, Indiana Published simultaneously in Canada

ISBN: 978-0-470-10485-9 Manufactured in the United States of America

10 9 8 7 6 5 4 3 2 1

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For Mary, Ethan, and Emma

Michael Alexander is a Microsoft Certified Application Developer(MCAD) with more than 14 years experience consulting and developingoffice solutions He currently lives in Plano, TX where he serves as a SeniorProgram Manager for a top technology firm In his spare time he runs a freetutorial site, www.datapigtechnologies.com, where he shares basicAccess and Excel tips to the Office community.

About the Author

vii

About the Author ix

Deciding Whether to Use Access or Excel 8

Contents

xi

Opening a Table in the Design View 17

Understanding the Relational Database Concept 30

Chapter 3 Beyond Select Queries 51

What Are the Hazards of Make-Table Queries? 62

Append Queries 68

Using the Query Design Grid to Create Your Crosstab

Finding and Removing Duplicate Records 96

Augmenting Field Values with Your Own Text 105

Removing Leading and Trailing Spaces from a String 109

Adding Your Own Text in Key Positions Within a String 112

Chapter 5 Working with Calculations and Dates 121

Using Calculations in Your Analysis 121

Using the Results of Aggregation in Calculations 124 Using the Results of One Calculation as an Expression

Using a Calculation as an Argument in a Function 125 Using the Expression Builder to Construct Calculations 126

Contents xiii

Common Calculation Errors 130 Understanding the Order of Operator Precedence 130

The Year, Month, Day, and Weekday Functions 139

Chapter 6 Performing Conditional Analysis 149

Working with Multiple Parameter Conditions 152

Using Parameters as Calculation Variables 155

Nesting IIf Functions for Multiple Conditions 163 Using IIf Functions to Create Crosstab Analyses 164

Part III Advanced Analysis Techniques 171 Chapter 7 Understanding and Using SQL 173

Getting Fancy with Advanced SQL Statements 179

Expanding Your Search with the Like Operator 180 Selecting Unique Values and Rows without Grouping 181

Grouping and Aggregating with the GROUP BY Clause 182

Setting Sort Order with the ORDER BY Clause 183

Performing Action Queries via SQL Statements 187

Creating Crosstabs with the TRANSFORM Statement 188

Creating a Table with the CREATE TABLE Statement 191 Manipulating Columns with the ALTER TABLE Statement 192

Altering a Column with the ALTER COLUMN Clause 193 Deleting a Column with the DROP COLUMN Clause 193

Chapter 8 Subqueries and Domain Aggregate Functions 195

Enhancing Your Analysis with Subqueries 196

Creating Subqueries without Typing SQL Statements 198

Using a Correlated Subquery as an Expression 205

Understanding the Different Domain Aggregate Functions 210

DMin and DMax 211

Examining the Syntax of Domain Aggregate Functions 212

Chapter 9 Running Descriptive Statistics in Access 221

Running Descriptive Statistics with Aggregate Queries 222

Pulling a Random Sampling from Your Dataset 229

Determining the Quartile Standing of a Record 233

Chapter 10 Analyzing Data with Pivot Tables and Pivot Charts 241

Creating an Advanced Pivot Table with Details 250

Working with Pivot Charts in Access 265

Part IV Automating Data Analysis 353 Chapter 11 Scheduling and Running Batch Analysis 275

Manipulating Forms, Queries, Reports, and Tables 283

Setting Up and Managing Batch Analysis 285

Scheduling Macros to Run Nightly 301

When to Use Command Lines to Schedule Tasks

Scheduling a Macro to Run Using a Command Line 308

Chapter 12 Leveraging VBA to Enhance Data Analysis 311

Creating and Using Custom Functions 312

Creating a Custom Function that Accepts Arguments 315

Controlling Analytical Processes with Forms 319

The Basics of Passing Data from a Form to a Query 320

Contents xvii

Processing Data Behind the Scenes 329

Advanced Techniques Using RunSQL Statements 332

Passing User-Defined Parameters from a Form to Your

Chapter 13 Query Performance, Database Corruption, and Other

Final Thoughts 339

Steps You Can Take to Optimize Query Performance 340

Compacting and Repairing Your Database Regularly 343

Watching for Corruption in Seemingly Normal Databases 344 Common Errors Associated with Database Corruption 345

Steps You Can Take to Prevent Database Corruption 348 Backing Up Your Database on a Regular Basis 348 Compacting and Repairing Your Database on a Regular

Avoiding Interruption of Service while Writing to Your

Never Working with a Database from Removable Media 350

Diversifying Your Knowledgebase with Online Resources 351

Part V Appendixes 353 Appendix A Data Analyst’s Function Reference 355 Appendix B Access VBA Fundamentals 397 Appendix C Error Message Reference 411

A big thank you to Katie Mohr for taking a chance on this project and beingsuch a wonderful project manager Many thanks to Kelly Talbot, Todd Meister,and the brilliant team of professionals who helped bring this book tofruition A special thank you to Mary who puts up with all my crazy projects.

Acknowledgments

xix

If you were to ask a random sampling of people what data analysis is, mostwould say that it is the process of calculating and summarizing data to get

an answer to a question In one sense, they are correct However, theactions they are describing represent only a small part of the processknown as data analysis

For example, if you were asked to analyze how much revenue in salesyour company made last month, what would you have to do in order tocomplete that analysis? You would just calculate and summarize the salesfor the month, right? Well, where would you get the sales data? Wherewould you store the data? Would you have to clean up the data when yougot it? How would you present your analysis: by week, by day, by loca-tion? The point being made here is that the process of data analysis is made

up of more than just calculating and summarizing data

A more representative definition of data analysis is the process of tematically collecting, transforming, and analyzing data in order to presentmeaningful conclusions To better understand this concept, think of dataanalysis as a process that encapsulates four fundamental actions: collec-tion, transformation, analysis, and presentation

sys-■■ Collection: Collection encompasses the gathering and storing ofdata—that is, where you obtain your data, how you will receiveyour data, how you will store your data, and how you will accessyour data when it comes time to perform some analysis

■■ Transformation: Transformation is the process of ensuring your data is uniform in structure, free from redundancy, and stable This

Introduction

xxi

generally entails things like establishing a table structure, cleaningtext, removing blanks, and standardizing data fields.

■■ Analysis: Analysis is the investigation of the component parts ofyour data and their relationships to your data source as a whole Youare analyzing your data when you are calculating, summarizing, cat-egorizing, comparing, contrasting, examining, or testing your data

■■ Presentation: In the context of data analysis, presentation deals withhow you make the content of your analysis available to a certainaudience That is, how you choose to display your results Someconsiderations that go along with presentation of your analysisinclude the platform you will use, the levels of visibility you willprovide, and the freedom you will give your audience to changetheir view

As you think about these four fundamental actions, think about this reality: Most analysts are severely limited to one tool—Excel This meansthat all of the complex actions involved in each of these fundamentals are mostly being done with and in Excel What’s the problem with that?Well Excel is not designed to do many of these actions However, manyanalysts are so limited in their toolsets that they often end up in hand-to-hand combat with their data, creating complex workarounds and ineffi-cient processes

What this book will highlight is that there are powerful functionalities inAccess that can help you go beyond your two-dimensional spreadsheetand liberate you from the daily grind of managing and maintaining redun-dant analytical processes Indeed, using Access for your data analysisneeds can help you streamline your analytical processes, increase yourproductivity, and analyze the larger datasets that have reached Excel’s limitations

Throughout this book, you will come to realize that Access is not a drydatabase program used only for storing data and building departmentalapplications Access possesses strong data analysis functionalities that areeasy to learn and certainly applicable to many types of organizations anddata systems

What to Expect from This Book

Within the first three chapters, you will be able to demonstrate proficiency

in Access, executing powerful analysis on large datasets that have longsince reached Excel’s limitations Within the first nine chapters, you will beable to add depth and dimension to your analysis with advanced Accessfunctions, building complex analytical processes with ease By the end of

the book, you will be able to create your own custom functions, performbatch analysis, and develop automated procedures that essentially run ontheir own.

After completing this book, you will be able to analyze large amounts ofdata in a meaningful way, quickly slice data into various views on the fly,automate redundant analysis, save time, and increase productivity

What to Not Expect from This Book

It’s important to note that there are aspects of Access and data analysis thatare outside the scope of this book While this book does cover the funda-mentals of Access, it is always in the light of data analysis and it is writtenfrom a data analyst’s point of view This is not meant to be an all-encom-passing book on Access That being said, if you are a first-time user ofAccess, you can feel confident that this book will provide you with a solidintroduction to Access that will leave you with valuable skills you can use

in your daily operations

This book is not meant to be a book on data management theory and bestpractices Nor is it meant to expound on high-level business intelligenceconcepts This is more of a “technician’s” book, providing hands-oninstruction that introduces Access as an analytical tool that can providepowerful solutions to common analytical scenarios and issues

Finally, while this book does contain a chapter that demonstrates varioustechniques to perform a whole range of statistical analysis, it is important

to note that this book does not cover statistics theory, methodology, or bestpractices

Skills Required for This Book

In order to get the most out of this book, it’s best that you have certain skillsbefore diving into the topics highlighted in this book The ideal candidatefor this book will have:

■■ Some experience working with data and familiarity with the basicconcepts of data analysis such as working with tables, aggregatingdata, and performing calculations

■■ Experience using Excel with a strong grasp of concepts such as tablestructures, filtering, sorting and using formulas

■■ Some basic knowledge of Access; enough to know it exists and tohave opened a database once or twice

Introduction xxiii

How This Book Is Organized

Part I: Fundamentals of Data Analysis in Access

Part I, which includes Chapters 1, 2, and 3, provides a condensed duction to Access Here, you will learn some of the basic fundamentals ofAccess, along with the essential query skills required throughout the rest ofthe book Topics covered in this Part are: relational database concepts,query basics, using aggregate queries, action queries, and Crosstabqueries

intro-Part II: Basic Analysis Techniques

Part II will introduce you to some of the basic analytical tools and niques available to you in Access Chapter 4 covers data transformation,providing examples of how to clean and shape raw data to fit your needs.Chapter 5 provides in-depth instruction on how to create and utilize customcalculations in your analysis Chapter 5 also shows you how to work withdates, using them in simple date calculations, or performing advanced timeanalysis Chapter 6 introduces you to some conditional analysis techniquesthat allow you to add logic to your analytical processes

tech-Part III: Advanced Analysis Techniques

Part III will demonstrate many of the advanced techniques that truly bringyour data analysis to the next level Chapter 7 covers the fundamentalsSQL statements Chapter 8 picks up from there and introduces you to sub-queries and domain aggregate functions Chapter 9 demonstrates many ofthe advanced statistical analysis you can perform using subqueries anddomain aggregate functions Chapter 10 provides you with an in-depthlook at using PivotTables and PivotCharts in Access

Part IV: Automating Data Analysis

Part IV takes you beyond manual analysis with queries and introduces you

to the world of automation Chapter 11 gives you an in-depth view of howmacros can help increase you productivity by running batch analysis.Chapter 12 demonstrates how a little coding with Visual Basic for Applica-tions (VBA) can help enhance data analysis Chapter 13 offers some finalthoughts and tips on query performance, database corruption, and how toget help in Access