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Beginning Big Data with Power BI and Excel 2013 (eBook)

Big Data Processing and Analysis Using PowerBI in Excel 2013

(Autor)

eBook Download: PDF
2015 | 1st ed.
XIX, 246 Seiten
Apress (Verlag)
978-1-4842-0529-7 (ISBN)

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Beginning Big Data with Power BI and Excel 2013 - Neil Dunlop
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In Beginning Big Data with Power BI and Excel 2013, you will learn to solve business problems by tapping the power of Microsoft's Excel and Power BI to import data from NoSQL and SQL databases and other sources, create relational data models, and analyze business problems through sophisticated dashboards and data-driven maps.

While Beginning Big Data with Power BI and Excel 2013 covers prominent tools such as Hadoop and the NoSQL databases, it recognizes that most small and medium-sized businesses don't have the Big Data processing needs of a Netflix, Target, or Facebook. Instead, it shows how to import data and use the self-service analytics available in Excel with Power BI. As you'll see through the book's numerous case examples, these tools-which you already know how to use-can perform many of the same functions as the higher-end Apache tools many people believe are required to carry out in Big Data projects.

Through instruction, insight, advice, and case studies, Beginning Big Data with Power BI and Excel 2013 will show you how to:

  • Import and mash up data from web pages, SQL and NoSQL databases, the Azure Marketplace and other sources.
  • Tap into the analytical power of PivotTables and PivotCharts and develop rel
ational data models to track trends and make predictions based on a wide range of data.
  • Understand basic statistics and use Excel with PowerBI to do sophisticated statistical analysis-including identifying trends and correlations.
  • Use SQL within Excel to do sophisticated queries across multiple tables, including NoSQL databases.
  • Create complex formulas to solve real-world business problems using Data Analysis Expressions (DAX).


  • Neil Dunlop is Professor of Business and Computer Information Systems, Berkeley City College, Berkeley, CA. The author has served as chair of the Business and Computer Information Systems Departments for many years. He has over thirty-five years experience as a computer programmer and software designer and is the author of three books on database management. He is listed in Marquis Who's Who in America and Who's Who in the World.
    In Beginning Big Data with Power BI and Excel 2013, you will learn to solve business problems by tapping the power of Microsoft's Excel and Power BI to import data from NoSQL and SQL databases and other sources, create relational data models, and analyze business problems through sophisticated dashboards and data-driven maps.While Beginning Big Data with Power BI and Excel 2013 covers prominent tools such as Hadoop and the NoSQL databases, it recognizes that most small and medium-sized businesses don't have the Big Data processing needs of a Netflix, Target, or Facebook. Instead, it shows how to import data and use the self-service analytics available in Excel with Power BI. As you'll see through the book's numerous case examples, these tools-which you already know how to use-can perform many of the same functions as the higher-end Apache tools many people believe are required to carry out in Big Data projects.Through instruction, insight, advice, andcase studies, Beginning Big Data with Power BI and Excel 2013 will show you how to:Import and mash up data from web pages, SQL and NoSQL databases, the Azure Marketplace and other sources.Tap into the analytical power of PivotTables and PivotCharts and develop relational data models to track trends and make predictions based on a wide range of data.Understand basic statistics and use Excel with PowerBI to do sophisticated statistical analysis including identifying trends and correlations.Use SQL within Excel to do sophisticated queries across multiple tables, including NoSQL databases.Create complex formulas to solve real-world business problems using Data Analysis Expressions (DAX).

    Neil Dunlop is Professor of Business and Computer Information Systems, Berkeley City College, Berkeley, CA. The author has served as chair of the Business and Computer Information Systems Departments for many years. He has over thirty-five years experience as a computer programmer and software designer and is the author of three books on database management. He is listed in Marquis Who’s Who in America and Who’s Who in the World.

    Contents at a Glance 4
    Contents 5
    About the Author 12
    About the Technical Reviewer 13
    Acknowledgments 14
    Introduction 15
    Chapter 1: Big Data 16
    Big Data As the Fourth Factor of Production 16
    Big Data As Natural Resource 16
    Data As Middle Manager 17
    Early Data Analysis 17
    First Time Line 17
    First Bar Chart and Time Series 18
    Cholera Map 18
    Modern Data Analytics 19
    Google Flu Trends 19
    Google Earth 20
    Tracking Malaria 20
    Big Data Cost Savings 20
    Big Data and Governments 20
    Predictive Policing 20
    A Cost-Saving Success Story 21
    Internet of Things or Industrial Internet 21
    Cutting Energy Costs at MIT 21
    The Big Data Revolution and Health Care 21
    The Medicalized Smartphone 22
    Improving Reliability of Industrial Equipment 23
    Big Data and Agriculture 23
    Cheap Storage 23
    Personal Computers and the Cost of Storage 23
    Review of File Sizes 23
    Data Keeps Expanding 24
    Relational Databases 24
    Normalization 24
    Database Software for Personal Computers 25
    The Birth of Big Data and NoSQL 26
    Hadoop Distributed File System (HDFS) 26
    Big Data 26
    The Three V’s 27
    The Data Life Cycle 27
    Apache Hadoop 27
    MapReduce Algorithm 27
    Hadoop Distributed File System (HDFS) 28
    Commercial Implementations of Hadoop 28
    CAP Theorem 28
    NoSQL 28
    Characteristics of NoSQL Data 28
    Implementations of NoSQL 29
    Spark 29
    Microsoft Self-Service BI 29
    Summary 29
    Chapter 2: Excel As Database and Data Aggregator 30
    From Spreadsheet to Database 30
    Interpreting File Extensions 31
    Using Excel As a Database 31
    Importing from Other Formats 33
    Opening Text Files in Excel 33
    Importing Data from XML 34
    Importing XML with Attributes 35
    Importing JSON Format 37
    Using the Data Tab to Import Data 38
    Importing Data from Tables on a Web Site 38
    Data Wrangling and Data Scrubbing 40
    Correcting Capitalization 40
    Splitting Delimited Fields 41
    Splitting Complex, Delimited Fields 44
    Removing Duplicates 45
    Input Validation 46
    Working with Data Forms 47
    Selecting Records 49
    Summary 49
    Chapter 3: Pivot Tables and Pivot Charts 50
    Recommended Pivot Tables in Excel 2013 50
    Defining a Pivot Table 51
    Defining Questions 52
    Creating a Pivot Table 52
    Changing the Pivot Table 54
    Creating a Breakdown of Sales by Salesperson for Each Day 55
    Showing Sales by Month 56
    Creating a Pivot Chart 57
    Adjusting Subtotals and Grand Totals 58
    Analyzing Sales by Day of Week 58
    Creating a Pivot Chart of Sales by Day of Week 60
    Using Slicers 62
    Adding a Time Line 63
    Importing Pivot Table Data from the Azure Marketplace 64
    Summary 69
    Chapter 4: Building a Data Model 70
    Enabling PowerPivot 70
    Relational Databases 72
    Database Terminology 72
    Creating a Data Model from Excel Tables 73
    Loading Data Directly into the Data Model 77
    Creating a Pivot Table from Two Tables 81
    Creating a Pivot Table from Multiple Tables 82
    Adding Calculated Columns 85
    Adding Calculated Fields to the Data Model 87
    Summary 89
    Chapter 5: Using SQL in Excel 91
    History of SQL 91
    NoSQL 91
    NewSQL 91
    SQL++ 92
    SQL Syntax 92
    SQL Aggregate Functions 93
    Subtotals 93
    Joining Tables 94
    Importing an External Database 94
    Specifying a JOIN Condition and Selected Fields 100
    Using SQL to Extract Summary Statistics 103
    Generating a Report of Total Order Value by Employee 105
    Using MSQuery 108
    Summary 112
    Chapter 6: Designing Reports with Power View 113
    Elements of the Power View Design Screen 113
    Considerations When Using Power View 114
    Types of Fields 114
    Understanding How Data Is Summarized 114
    A Single Table Example 115
    Viewing the Data in Different Ways 118
    Creating a Bar Chart for a Single Year 119
    Column Chart 120
    Displaying Multiple Years 121
    Adding a Map 122
    Using Tiles 123
    Relational Example 125
    Customer and City Example 129
    Showing Orders by Employee 134
    Aggregating Orders by Product 136
    Summary 140
    Chapter 7: Calculating with Data Analysis Expressions (DAX) 141
    Understanding Data Analysis Expressions 141
    DAX Operators 142
    Summary of Key DAX Functions Used in This Chapter 142
    Updating Formula Results 142
    Creating Measures or Calculated Fields 144
    Analyzing Profitability 146
    Using the SUMX Function 149
    Using the CALCULATE Function 150
    Calculating the Store Sales for 2009 152
    Creating a KPI for Profitability 154
    Creating a Pivot Table Showing Profitability by Product Line 156
    Summary 158
    Chapter 8: Power Query 159
    Installing Power Query 159
    Key Options on Power Query Ribbon 160
    Working with the Query Editor 160
    Key Options on the Query Editor Home Ribbon 161
    A Simple Population 163
    Performance of S& P 500 Stock Index
    Importing CSV Files from a Folder 169
    Group By 174
    Importing JSON 176
    Summary 186
    Chapter 9: Power Map 187
    Installing Power Map 187
    Plotting a Map 187
    Key Power Map Ribbon Options 188
    Troubleshooting 189
    Plotting Multiple Statistics 194
    Adding a 2D Chart 198
    Showing Two or More Values 205
    Creating a 2D Chart 207
    Summary 215
    Chapter 10: Statistical Calculations 216
    Recommended Analytical Tools in 2013 216
    Customizing the Status Bar 218
    Inferential Statistics 219
    Review of Descriptive Statistics 219
    Calculating Descriptive Statistics 220
    Measures of Dispersion 220
    Excel Statistical Functions 221
    Charting Data 221
    Excel Analysis ToolPak 221
    Enabling the Excel Analysis ToolPak 221
    A Simple Example 223
    Other Analysis ToolPak Functions 227
    Using a Pivot Table to Create a Histogram 227
    Scatter Chart 232
    Summary 237
    Chapter 11: HDInsight 238
    Getting a Free Azure Account 238
    Importing Hadoop Files into Power Query 239
    Creating an Azure Storage Account 239
    Provisioning a Hadoop Cluster 242
    Importing into Excel 247
    Creating a Pivot Table 251
    Creating a Map in Power Map 252
    Summary 254
    Index 255

    Erscheint lt. Verlag 4.10.2015
    Zusatzinfo XIX, 246 p. 284 illus.
    Verlagsort Berkeley
    Sprache englisch
    Themenwelt Mathematik / Informatik Informatik Datenbanken
    Mathematik / Informatik Informatik Netzwerke
    Informatik Office Programme Excel
    Mathematik / Informatik Informatik Software Entwicklung
    Mathematik / Informatik Informatik Theorie / Studium
    ISBN-10 1-4842-0529-4 / 1484205294
    ISBN-13 978-1-4842-0529-7 / 9781484205297
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