Getting started with data science: making sense of data with analytics
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| Format: | Buch |
| Sprache: | English |
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Boston
IBM Press
[2016]
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xxx, 573 Seiten Illustrationen, Diagramme, Karten |
| ISBN: | 9780133991024 0133991024 |
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| adam_text | Contents-at-a-G lance
Preface xix
Chapter 1 The Bazaar of Storytellers 1
Chapter 2 Data in the 24/7 Connected World 29
Chapter 3 The Deliverable 49
Chapter 4 Serving Tables 99
Chapter 5 Graphic Details 141
Chapter 6 Hypothetically Speaking 187
Chapter 7 Why Tall Parents Don’t Have Even Taller Children 235
Chapter 8 To Be or Not to Be 299
Chapter 9 Categorically Speaking About Categorical Data 349
Chapter 10 Spatial Data Analytics 415
Chapter 11 Doing Serious Time with Time Series 463
Chapter 12 Data Mining for Gold 525
Index
553
Contents
Preface xix
Chapter 1 The Bazaar of Storytellers........................................................1
Data Science: The Sexiest Job in the 21st Century....................................4
Storytelling at Google and Walmart....................................................6
Getting Started with Data Science.....................................................8
Do We Need Another Book on Analytics?...........................................8
Repeat, Repeat, Repeat, and Simplify...........................................10
Chapters’ Structure and Features...............................................10
Analytics Software Used.......................................................-12
What Makes Someone a Data Scientist?.................................................12
Existential Angst of a Data Scientist..........................................15
Data Scientists: Rarer Than Unicorns...........................................16
Beyond the Big Data Hype.............................................................12
Big Data: Beyond Cheerleadmg...................................................18
Big Data Hubris................................................................19
Leading by Miles...............................................................20
Predicting Pregnancies, Missing Abortions......................................20
What’s Beyond This Book?.............................................................21
Summary.............................................................................-23
Endnotes.............................................................................24
Chapter 2 Data in the 24/7 Connected World.................................................29
The Liberated Data: The Open Data....................................................20
The Caged Data.......................................................................20
Big Data Is Big News.................................................................21
It’s Not the Size of Big Data; It’s What You Do with It..............................22
Free Data as in Free Lunch...........................................................24
FRED...........................................................................34
Quandl........................................................................ 38
U.S. Census Bureau and Other National Statistical Agencies.....................38
Contents
xiii
Search-Based Internet Data............................................................39
Google Trends...................................................................40
Google Correlate................................................................42
, Survey Data...........................................................................44
PEW Surveys.....................................................................44
ICPSR...........................................................................45
Summary...............................................................................45
Endnotes..............................................................................46
Chapter 3 The Deliverable...................................................................49
The Final Deliverable.................................................................52
What Is the Research Question?..................................................53
What Answers Are Needed?........................................................54
How Have Others Researched the Same Question in the Past?.......................54
What Information Do You Need to Answer the Question?............................58
What Analytical Techniques/Methods Do You Need?.................................58
The Narrative.........................................................................59
The Report Structure............................................................60
Have You Done Your Job as a Writer?.............................................62
Building Narratives with Data.........................................................62
“Big Data, Big Analytics, Big Opportunity ......................................63
Urban Transport and Housing Challenges..........................................68
Human Development in South Asia.................................................77
The Big Move....................................................................82
Summary...............................................................................95
Endnotes..............................................................................96
Chapter 4 Serving Tables...............................................*..................99
2014: The Year of Soccer and Brazil..................................................100
Using Percentages Is Better Than Using Raw Numbers.............................104
Data Cleaning..................................................................106
Weighted Data..................................................................106
Cross Tabulations..............................................................109
Going Beyond the Basics in Tables..............................................113
Seeing Whether Beauty Pays...........................................................115
DataSet........................................................................117
What Determines Teaching Evaluations?..........................................118
Does Beauty Affect Teaching Evaluations?.......................................124
Putting It All on (in) a Table.................................................125
Generating Output with Stata.........................................................129
Summary Statistics Using Built-In Stata........................................130
Using Descriptive Statistics...................................................130
Weighted Statistics............................................................134
xiv Contents
Correlation Matrix.............................................................134
Reproducing the Results for the Hamermesh and Parker Paper.....................135
Statistical Analysis Using Custom Tables.......................................136
Summary..............................................................................137
Endnotes.............................................................................139
Chapters Graphic Details...................................................................141
Telling Stories with Figures.........................................................142
Data Types.....................................................................144
Teaching Ratings.....................................................................144
The Congested Lives in Big Cities....................................................168
Summary..............................................................................185
Endnotes.............................................................................185
Chapter 6 Hypothetically Speaking..........................................................187
Random Numbers and Probability Distributions.........................................188
Casino Royale: Roll the Dice.........................................................190
Normal Distribution..................................................................194
The Student Who Taught Everyone Else.................................................195
Statistical Distributions in Action..................................................196
Z-Transformation...............................................................198
Probability of Getting a High or Low Course Evaluation.........................199
Probabilities with Standard Normal Table.......................................201
Hypothetically Yours.................................................................205
Consistently Better or Happenstance............................................205
Mean and Not So Mean Differences.....1.........................................206
Handling Rejections............................................................207
The Mean and Kind Differences........................................................211
Comparing a Sample Mean When the Population SD Is Known........................211
Left Tail Between the Legs.....................................................214
Comparing Means with Unknown Population SD.....................................217
Comparing Two Means with Unequal Variances.....................................219
Comparing Two Means with Equal Variances.......................................223
Worked-Out Examples of Hypothesis Testing............................................226
Best Buy-Apple Store Comparison................................................226
Assuming Equal Variances.......................................................227
Exercises for Comparison of Means....................................................228
Regression for Hypothesis Testing....................................................228
Analysis of Variance.................................................................231
Significantly Correlated.............................................................232
Summary..............................................................................233
Endnotes.............................................................................234
Contents
XV
Chapter 7 Why Tall Parents Don’t Have Even
Taller Children...........................................................235
The Department of Obvious Conclusions.................................................235
Why Regress?....................................................................236
Introducing Regression Models.........................................................238
All Else Being Equal............................................................239
Holding Other Factors Constant..................................................242
Spuriously Correlated...........................................................244
A Step-By-Step Approach to Regression...........................................244
Learning to Speak Regression....................................................247
The Math Behind Regression......................................................248
Ordinary Least Squares Method...................................................250
Regression in Action..................................................................259
This Just In: Bigger Homes Sell for More........................................260
Does Beauty Pay? Ask the Students...............................................272
Survey Data, Weights, and Independence of Observations..........................276
What Determines Household Spending on Alcohol and Food..........................279
What Influences Household Spending on Food?.....................................285
Advanced Topics.......................................................................289
Homoskedasticity................................................................289
Multicollinearity...............................................................293
Summary...............................................................................296
Endnotes..............................................................................296
Chapter 8 To Be or Not to Be................................................................299
To Smoke or Not to Smoke: That Is the Question........................................300
Binary Outcomes.................................................................301
Binary Dependent Variables......................................................301
Let’s Question the Decision to Smoke or Not.....................................303
Smoking Data Set................................................................304
Exploratory Data Analysis.............................................................305
What Makes People Smoke: Asking Regression for Answers................................307
Ordinary Least Squares Regression...............................................307
Interpreting Models at the Margins..............................................310
The Logit Model.......................................................................311
Interpreting Odds in a Logit Model....................................................315
Probit Model..........................................................................321
Interpreting the Probit Model...................................................324
Using Zelig for Estimation and Post-Estimation Strategies.......................329
Estimating Logit Models for Grouped Data..............................................334
Using SPSS to Explore the Smoking Data Set............................................338
Regression Analysis in SPSS.....................................................341
Estimating Logit and Probit Models in SPSS......................................343
Summary7..............................................................................346
Endnotes..............................................................................347
XVI
Contents
Chapter 9 Categorically Speaking About Categorical Data „ . . .349
What Is Categorical Data?..............................................................3 ֊ I
Analyzing Categorical Data.............................................................352
Econometric Models of Binomial Data....................................................354
Estimation of Binary Logit Models.................................................355
Odds Ratio........................................................................356
Log of Odds Ratio.................................................................357
Interpreting Binary Logit Models..................................................357
Statistical Inference of Binary Logit Models......................................362
How I Met Your Mother? Analyzing Survey Data............................................363
A Blind Date with the Pew Online Dating Data Set..................................365
Demographics of Affection.........................................................365
High-Techies......................................................................368
Romancing the Internet............................................................368
Dating Models.....................................................................371
Multinomial Logit Models................................................................378
Interpreting Multinomial Logit Models.............................................379
Choosing an Online Dating Service.................................................380
Pew Phone Type Model..............................................................382
Why Some Women Work Full-Time and Others Don’t....................................389
Conditional Logit Models................................................................398
Random Utility Model..............................................................400
Independence From Irrelevant Alternatives.........................................404
Interpretation of Conditional Logit Models........................................405
Estimating Logit Models in SPSS...................................................410
Summary.................................................................................411
Endnotes................................................................................413
Chapter 10 Spatial Data Analytics..............................................................415
Fundamentals of GIS.....................................................................417
GIS Platforms...........................................................................418
Freeware GIS......................................................................420
GIS Data Structure................................................................420
GIS Applications in Business Research...................................................420
Retail Research...................................................................421
Hospitality and Tourism Research..................................................422
Lifestyle Data: Consumer Health Profiling.........................................423
Competitor Location Analysis......................................................423
Market Segmentation...............................................................423
Spatial Analysis of Urban Challenges....................................................424
The Hard Truths About Public Transit in North America.............................424
Toronto Is a City Divided into the Haves, Will Haves, and Have Nots...............429
Contents xvii
Income Disparities in Urban Canada.............................................434
Where Is Toronto’s Missing Middle Class? It Has Suburbanized Out of Toronto....435
Adding Spatial Analytics to Data Science.............................................444
Race and Space in Chicago............................................................447
Developing Research Questions..................................................448
Race, Space, and Poverty.......................................................450
Race, Space, and Commuting.....................................................454
Regression with Spatial Lags...................................................457
Summary..............................................................................460
Endnotes.............................................................................461
Chapter 11 Doing Serious Time with Time Series.............................................463
Introducing Time Series Data and How to Visualize It.................................464
How Is Time Series Data Different?...................................................468
Starting with Basic Regression Models................................................471
What Is Wrong with Using OLS Models for Time Series Data?............................473
Newey-West Standard Errors.....................................................473
Regressing Prices with Robust Standard Errors..................................474
Time Series Econometrics.............................................................478
Stationary Time Series.........................................................479
Autocorrelation Function (ACF).................................................479
Partial Autocorrelation Function (PCF).........................................481
White Noise Tests..............................................................483
Augmented Dickey Fuller Test...................................................483
Econometric Models for Time Senes Data...............................................484
Correlation Diagnostics........................................................485
Invertible Time Series and Lag Operators.......................................485
The ARMA Model.................................................................487
ARIMA Models...................................................................487
Distributed Lag and VAR Models.................................................488
Applying Time Series Tools to Housing Construction...................................492
Macro֊Economic and SocioDemographic Variables Influencing
Housing Starts..............................................................498
Estimating Time Series Models to Forecast New Housing Construction...................500
OLS Models.....................................................................501
Distributed Lag Model..........................................................505
Outof-Sample Forecasting with Vector Autoregressive Models.....................508
ARIMA Models...................................................................510
Summary..............................................................................522
Endnotes.............................................................................524
Contents
xviii
Chapter 12 Data Mining for Gold.............................................................525
Can Cheating on Your Spouse Kill You?.................................................526
Are Cheating Men Alpha Males?....................................................526
UnFair Comments: New Evidence Critiques Fair’s Research.........................527
Data Mining: An Introduction...........................................................527
Seven Steps Down the Data Mine........................................................529
Establishing Data Mining Goals...................................................529
Selecting Data...................................................................529
Preprocessing Data...............................................................530
Transforming Data................................................................530
Storing Data.....................................................................531
Mining Data......................................................................531
Evaluating Mining Results........................................................531
Rattle Your Data.......................................................................531
What Does Religiosity Have to Do with Extramarital Affairs?......................533
The Principal Components of an Extramarital Affair...............................539
Will It Rain Tomorrow? Using PCA For Weather Forecasting.........................540
Do Men Have More Affairs Than Females7...........................................542
Two Kinds of People: Those Who Have Affairs, and Those Who Don’t.................542
Models to Mine Data with Rattle..................................................544
Summary................................................................................550
Endnotes...............................................................................550
Index
553
Contents-at-a-G lance
Preface xix
Chapter 1 The Bazaar of Storytellers 1
Chapter 2 Data in the 24/7 Connected World 29
Chapter 3 The Deliverable 49
Chapter 4 Serving Tables 99
Chapter 5 Graphic Details 141
Chapter 6 Hypothetically Speaking 187
Chapter 7 Why Tall Parents Don’t Have Even Taller Children 235
Chapter 8 To Be or Not to Be 299
Chapter 9 Categorically Speaking About Categorical Data 349
Chapter 10 Spatial Data Analytics 415
Chapter 11 Doing Serious Time with Time Series 463
Chapter 12 Data Mining for Gold 525
Index
553
Contents
Preface xix
Chapter 1 The Bazaar of Storytellers........................................................1
Data Science: The Sexiest Job in the 21st Century....................................4
Storytelling at Google and Walmart....................................................6
Getting Started with Data Science.....................................................8
Do We Need Another Book on Analytics?...........................................8
Repeat, Repeat, Repeat, and Simplify...........................................10
Chapters’ Structure and Features...............................................10
Analytics Software Used.......................................................-12
What Makes Someone a Data Scientist?.................................................12
Existential Angst of a Data Scientist..........................................15
Data Scientists: Rarer Than Unicorns...........................................16
Beyond the Big Data Hype.............................................................12
Big Data: Beyond Cheerleadmg...................................................18
Big Data Hubris................................................................19
Leading by Miles...............................................................20
Predicting Pregnancies, Missing Abortions......................................20
What’s Beyond This Book?.............................................................21
Summary.............................................................................-23
Endnotes.............................................................................24
Chapter 2 Data in the 24/7 Connected World.................................................29
The Liberated Data: The Open Data....................................................20
The Caged Data.......................................................................20
Big Data Is Big News.................................................................21
It’s Not the Size of Big Data; It’s What You Do with It..............................22
Free Data as in Free Lunch...........................................................24
FRED...........................................................................34
Quandl........................................................................ 38
U.S. Census Bureau and Other National Statistical Agencies.....................38
Contents
xiii
Search-Based Internet Data............................................................39
Google Trends...................................................................40
Google Correlate................................................................42
, Survey Data...........................................................................44
PEW Surveys.....................................................................44
ICPSR...........................................................................45
Summary...............................................................................45
Endnotes..............................................................................46
Chapter 3 The Deliverable...................................................................49
The Final Deliverable.................................................................52
What Is the Research Question?..................................................53
What Answers Are Needed?........................................................54
How Have Others Researched the Same Question in the Past?.......................54
What Information Do You Need to Answer the Question?............................58
What Analytical Techniques/Methods Do You Need?.................................58
The Narrative.........................................................................59
The Report Structure............................................................60
Have You Done Your Job as a Writer?.............................................62
Building Narratives with Data.........................................................62
“Big Data, Big Analytics, Big Opportunity ......................................63
Urban Transport and Housing Challenges..........................................68
Human Development in South Asia.................................................77
The Big Move....................................................................82
Summary...............................................................................95
Endnotes..............................................................................96
Chapter 4 Serving Tables...............................................*..................99
2014: The Year of Soccer and Brazil..................................................100
Using Percentages Is Better Than Using Raw Numbers.............................104
Data Cleaning..................................................................106
Weighted Data..................................................................106
Cross Tabulations..............................................................109
Going Beyond the Basics in Tables..............................................113
Seeing Whether Beauty Pays...........................................................115
DataSet........................................................................117
What Determines Teaching Evaluations?..........................................118
Does Beauty Affect Teaching Evaluations?.......................................124
Putting It All on (in) a Table.................................................125
Generating Output with Stata.........................................................129
Summary Statistics Using Built-In Stata........................................130
Using Descriptive Statistics...................................................130
Weighted Statistics............................................................134
xiv Contents
Correlation Matrix.............................................................134
Reproducing the Results for the Hamermesh and Parker Paper.....................135
Statistical Analysis Using Custom Tables.......................................136
Summary..............................................................................137
Endnotes.............................................................................139
Chapters Graphic Details...................................................................141
Telling Stories with Figures.........................................................142
Data Types.....................................................................144
Teaching Ratings.....................................................................144
The Congested Lives in Big Cities....................................................168
Summary..............................................................................185
Endnotes.............................................................................185
Chapter 6 Hypothetically Speaking..........................................................187
Random Numbers and Probability Distributions.........................................188
Casino Royale: Roll the Dice.........................................................190
Normal Distribution..................................................................194
The Student Who Taught Everyone Else.................................................195
Statistical Distributions in Action..................................................196
Z-Transformation...............................................................198
Probability of Getting a High or Low Course Evaluation.........................199
Probabilities with Standard Normal Table.......................................201
Hypothetically Yours.................................................................205
Consistently Better or Happenstance............................................205
Mean and Not So Mean Differences.....1.........................................206
Handling Rejections............................................................207
The Mean and Kind Differences........................................................211
Comparing a Sample Mean When the Population SD Is Known........................211
Left Tail Between the Legs.....................................................214
Comparing Means with Unknown Population SD.....................................217
Comparing Two Means with Unequal Variances.....................................219
Comparing Two Means with Equal Variances.......................................223
Worked-Out Examples of Hypothesis Testing............................................226
Best Buy-Apple Store Comparison................................................226
Assuming Equal Variances.......................................................227
Exercises for Comparison of Means....................................................228
Regression for Hypothesis Testing....................................................228
Analysis of Variance.................................................................231
Significantly Correlated.............................................................232
Summary..............................................................................233
Endnotes.............................................................................234
Contents
XV
Chapter 7 Why Tall Parents Don’t Have Even
Taller Children...........................................................235
The Department of Obvious Conclusions.................................................235
Why Regress?....................................................................236
Introducing Regression Models.........................................................238
All Else Being Equal............................................................239
Holding Other Factors Constant..................................................242
Spuriously Correlated...........................................................244
A Step-By-Step Approach to Regression...........................................244
Learning to Speak Regression....................................................247
The Math Behind Regression......................................................248
Ordinary Least Squares Method...................................................250
Regression in Action..................................................................259
This Just In: Bigger Homes Sell for More........................................260
Does Beauty Pay? Ask the Students...............................................272
Survey Data, Weights, and Independence of Observations..........................276
What Determines Household Spending on Alcohol and Food..........................279
What Influences Household Spending on Food?.....................................285
Advanced Topics.......................................................................289
Homoskedasticity................................................................289
Multicollinearity...............................................................293
Summary...............................................................................296
Endnotes..............................................................................296
Chapter 8 To Be or Not to Be................................................................299
To Smoke or Not to Smoke: That Is the Question........................................300
Binary Outcomes.................................................................301
Binary Dependent Variables......................................................301
Let’s Question the Decision to Smoke or Not.....................................303
Smoking Data Set................................................................304
Exploratory Data Analysis.............................................................305
What Makes People Smoke: Asking Regression for Answers................................307
Ordinary Least Squares Regression...............................................307
Interpreting Models at the Margins..............................................310
The Logit Model.......................................................................311
Interpreting Odds in a Logit Model....................................................315
Probit Model..........................................................................321
Interpreting the Probit Model...................................................324
Using Zelig for Estimation and Post-Estimation Strategies.......................329
Estimating Logit Models for Grouped Data..............................................334
Using SPSS to Explore the Smoking Data Set............................................338
Regression Analysis in SPSS.....................................................341
Estimating Logit and Probit Models in SPSS......................................343
Summary7..............................................................................346
Endnotes..............................................................................347
XVI
Contents
Chapter 9 Categorically Speaking About Categorical Data „ . . .349
What Is Categorical Data?..............................................................3 ֊ I
Analyzing Categorical Data.............................................................352
Econometric Models of Binomial Data....................................................354
Estimation of Binary Logit Models.................................................355
Odds Ratio........................................................................356
Log of Odds Ratio.................................................................357
Interpreting Binary Logit Models..................................................357
Statistical Inference of Binary Logit Models......................................362
How I Met Your Mother? Analyzing Survey Data............................................363
A Blind Date with the Pew Online Dating Data Set..................................365
Demographics of Affection.........................................................365
High-Techies......................................................................368
Romancing the Internet............................................................368
Dating Models.....................................................................371
Multinomial Logit Models................................................................378
Interpreting Multinomial Logit Models.............................................379
Choosing an Online Dating Service.................................................380
Pew Phone Type Model..............................................................382
Why Some Women Work Full-Time and Others Don’t....................................389
Conditional Logit Models................................................................398
Random Utility Model..............................................................400
Independence From Irrelevant Alternatives.........................................404
Interpretation of Conditional Logit Models........................................405
Estimating Logit Models in SPSS...................................................410
Summary.................................................................................411
Endnotes................................................................................413
Chapter 10 Spatial Data Analytics..............................................................415
Fundamentals of GIS.....................................................................417
GIS Platforms...........................................................................418
Freeware GIS......................................................................420
GIS Data Structure................................................................420
GIS Applications in Business Research...................................................420
Retail Research...................................................................421
Hospitality and Tourism Research..................................................422
Lifestyle Data: Consumer Health Profiling.........................................423
Competitor Location Analysis......................................................423
Market Segmentation...............................................................423
Spatial Analysis of Urban Challenges....................................................424
The Hard Truths About Public Transit in North America.............................424
Toronto Is a City Divided into the Haves, Will Haves, and Have Nots...............429
Contents xvii
Income Disparities in Urban Canada.............................................434
Where Is Toronto’s Missing Middle Class? It Has Suburbanized Out of Toronto....435
Adding Spatial Analytics to Data Science.............................................444
Race and Space in Chicago............................................................447
Developing Research Questions..................................................448
Race, Space, and Poverty.......................................................450
Race, Space, and Commuting.....................................................454
Regression with Spatial Lags...................................................457
Summary..............................................................................460
Endnotes.............................................................................461
Chapter 11 Doing Serious Time with Time Series.............................................463
Introducing Time Series Data and How to Visualize It.................................464
How Is Time Series Data Different?...................................................468
Starting with Basic Regression Models................................................471
What Is Wrong with Using OLS Models for Time Series Data?............................473
Newey-West Standard Errors.....................................................473
Regressing Prices with Robust Standard Errors..................................474
Time Series Econometrics.............................................................478
Stationary Time Series.........................................................479
Autocorrelation Function (ACF).................................................479
Partial Autocorrelation Function (PCF).........................................481
White Noise Tests..............................................................483
Augmented Dickey Fuller Test...................................................483
Econometric Models for Time Senes Data...............................................484
Correlation Diagnostics........................................................485
Invertible Time Series and Lag Operators.......................................485
The ARMA Model.................................................................487
ARIMA Models...................................................................487
Distributed Lag and VAR Models.................................................488
Applying Time Series Tools to Housing Construction...................................492
Macro֊Economic and SocioDemographic Variables Influencing
Housing Starts..............................................................498
Estimating Time Series Models to Forecast New Housing Construction...................500
OLS Models.....................................................................501
Distributed Lag Model..........................................................505
Outof-Sample Forecasting with Vector Autoregressive Models.....................508
ARIMA Models...................................................................510
Summary..............................................................................522
Endnotes.............................................................................524
Contents
xviii
Chapter 12 Data Mining for Gold.............................................................525
Can Cheating on Your Spouse Kill You?.................................................526
Are Cheating Men Alpha Males?....................................................526
UnFair Comments: New Evidence Critiques Fair’s Research.........................527
Data Mining: An Introduction...........................................................527
Seven Steps Down the Data Mine........................................................529
Establishing Data Mining Goals...................................................529
Selecting Data...................................................................529
Preprocessing Data...............................................................530
Transforming Data................................................................530
Storing Data.....................................................................531
Mining Data......................................................................531
Evaluating Mining Results........................................................531
Rattle Your Data.......................................................................531
What Does Religiosity Have to Do with Extramarital Affairs?......................533
The Principal Components of an Extramarital Affair...............................539
Will It Rain Tomorrow? Using PCA For Weather Forecasting.........................540
Do Men Have More Affairs Than Females7...........................................542
Two Kinds of People: Those Who Have Affairs, and Those Who Don’t.................542
Models to Mine Data with Rattle..................................................544
Summary................................................................................550
Endnotes...............................................................................550
Index
553
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| any_adam_object | 1 |
| author | Haider, Murtaza |
| author_GND | (DE-588)1081992573 |
| author_facet | Haider, Murtaza |
| author_role | aut |
| author_sort | Haider, Murtaza |
| author_variant | m h mh |
| building | Verbundindex |
| bvnumber | BV043333644 |
| classification_rvk | QH 234 ST 530 |
| ctrlnum | (OCoLC)955279203 (DE-599)BVBBV043333644 |
| discipline | Informatik Wirtschaftswissenschaften |
| format | Book |
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| genre_facet | Lehrbuch |
| id | DE-604.BV043333644 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:23:19Z |
| institution | BVB |
| isbn | 9780133991024 0133991024 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028753755 |
| oclc_num | 955279203 |
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| owner_facet | DE-11 DE-355 DE-BY-UBR DE-739 DE-29T DE-573 DE-898 DE-BY-UBR |
| physical | xxx, 573 Seiten Illustrationen, Diagramme, Karten |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | IBM Press |
| record_format | marc |
| spelling | Haider, Murtaza Verfasser (DE-588)1081992573 aut Getting started with data science making sense of data with analytics Murtaza Haider Boston IBM Press [2016] © 2016 xxx, 573 Seiten Illustrationen, Diagramme, Karten txt rdacontent n rdamedia nc rdacarrier Literaturangaben Data mining Big data Big Data (DE-588)4802620-7 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Big Data (DE-588)4802620-7 s Data Mining (DE-588)4428654-5 s Datenanalyse (DE-588)4123037-1 s b DE-604 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028753755&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028753755&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Haider, Murtaza Getting started with data science making sense of data with analytics Data mining Big data Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd Datenanalyse (DE-588)4123037-1 gnd |
| subject_GND | (DE-588)4802620-7 (DE-588)4428654-5 (DE-588)4123037-1 (DE-588)4123623-3 |
| title | Getting started with data science making sense of data with analytics |
| title_auth | Getting started with data science making sense of data with analytics |
| title_exact_search | Getting started with data science making sense of data with analytics |
| title_full | Getting started with data science making sense of data with analytics Murtaza Haider |
| title_fullStr | Getting started with data science making sense of data with analytics Murtaza Haider |
| title_full_unstemmed | Getting started with data science making sense of data with analytics Murtaza Haider |
| title_short | Getting started with data science |
| title_sort | getting started with data science making sense of data with analytics |
| title_sub | making sense of data with analytics |
| topic | Data mining Big data Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd Datenanalyse (DE-588)4123037-1 gnd |
| topic_facet | Data mining Big data Big Data Data Mining Datenanalyse Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028753755&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028753755&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT haidermurtaza gettingstartedwithdatasciencemakingsenseofdatawithanalytics |
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