Be data literate: the data literacy skills everyone needs to succeed
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
London ; New York, NY ; New Delhi
KoganPage
[2021]
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Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | Literaturangaben |
Beschreibung: | xiv, 223 Seiten Illustrationen, Diagramme, Karten |
ISBN: | 9781789668032 9781789668018 |
Internformat
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CONTENTS List of figures xi About the author xii Preface xiii 01 The world of data 1 Data: The world we live in 2 Data: The skills gap 6 Data: Why is there a skills gap? 8 Data: What’s next? 13 Chapter summary 14 Notes 15 02 The four levels of analytics 17 Data and analytics - there are four levels? 17 The four levels of analytics 18 Level 1: Descriptive analytics 20 Level 2: Diagnostic analytics 23 Level 3: Predictive analytics 26 Level 4: Prescriptive analytics 29 Real-world examples of the four levels of analytics 30 Chapter summary 33 Notes 34 03 Defining data literacy 35 Characteristic 1: Reading data 36 Characteristic 2: Working with data 39 Characteristic 3: Analysing data 44 Characteristic 4: Communicating with data 47 Chapter summary 49 Notes 50
viii CONTENTS 04 The data literacy umbrella 51 Data and analytical strategy 53 Data literacy and data science 54 Data literacy and data visualization 57 Data literacy and executive teams 63 Data literacy and culture 65 Data literacy and data quality 66 Data literacy and data governance 67 Data literacy and ethics and regulation 68 Chapter summary 72 Notes 73 05 Reading and speaking the language of data 75 Reading data 79 Data fluency 82 The data dictionary 85 Reading data and data fluency strategy 86 Organizational example 87 Chapter summary 89 Notes 89 06 Combining data literacy and the four levels of analytics 91 Data literacy and descriptive analytics 91 Data literacy and diagnostic analytics 96 Data literacy and predictive analytics 104 Data literacy and prescriptive analytics 108 Data literacy and the four levels of analytics - the holistic puzzle 111 Chapter summary 112 Notes 113 07 The steps of data literacy learning 115 The role of leadership and data literacy learning 116 The role of data and analytical strategy and data literacy learning 118
CONTENTS A data literacy learning framework and approach 120 Learning for the four characteristics of data literacy 125 Learning for a strong data literate culture 128 Other areas of data literacy learning and focus 131 Chapter summary 133 Notes 133 08 The three Cs of data literacy 135 The first C of data literacy: Curiosity 136 The second C of data literacy: Creativity 144 The third C of data literacy: Critical thinking 150 Reading data 152 Working with data 152 Analyzing data 153 Communicating with data 153 Chapter summary 154 Notes 155 09 Data informed decision-making 157 Steps of the data informed decision-making framework 158 Step 1: Ask 160 Step 2: Acquire 162 Step 3: Analyze 164 Step 4: Integrate 167 Step 5: Decide 171 Step 6: Iterate 173 Chapter summary and example 175 Notes 177 10 Data literacy and data and analytical strategy 179 Data driven culture 180 Business intelligence 182 Artificial intelligence 185 Machine learning and algorithms 188 Big data 190 ix
x CONTENTS Embedded analytics 191 The Cloud 193 Edge analytics 194 Geo analytics 195 Chapter summary 196 Notes 197 11 Begin your data and analytics journey 199 COVID-19 and data and analytics 200 Making a recipe 203 Focus on proactive versus reactive analytics 206 Start with the basics 208 The gamification of data and analytics 210 Find something that interests you and run to it 211 Find your why 212 Chapter summary 214 Notes 214 Index 217 |
adam_txt |
CONTENTS List of figures xi About the author xii Preface xiii 01 The world of data 1 Data: The world we live in 2 Data: The skills gap 6 Data: Why is there a skills gap? 8 Data: What’s next? 13 Chapter summary 14 Notes 15 02 The four levels of analytics 17 Data and analytics - there are four levels? 17 The four levels of analytics 18 Level 1: Descriptive analytics 20 Level 2: Diagnostic analytics 23 Level 3: Predictive analytics 26 Level 4: Prescriptive analytics 29 Real-world examples of the four levels of analytics 30 Chapter summary 33 Notes 34 03 Defining data literacy 35 Characteristic 1: Reading data 36 Characteristic 2: Working with data 39 Characteristic 3: Analysing data 44 Characteristic 4: Communicating with data 47 Chapter summary 49 Notes 50
viii CONTENTS 04 The data literacy umbrella 51 Data and analytical strategy 53 Data literacy and data science 54 Data literacy and data visualization 57 Data literacy and executive teams 63 Data literacy and culture 65 Data literacy and data quality 66 Data literacy and data governance 67 Data literacy and ethics and regulation 68 Chapter summary 72 Notes 73 05 Reading and speaking the language of data 75 Reading data 79 Data fluency 82 The data dictionary 85 Reading data and data fluency strategy 86 Organizational example 87 Chapter summary 89 Notes 89 06 Combining data literacy and the four levels of analytics 91 Data literacy and descriptive analytics 91 Data literacy and diagnostic analytics 96 Data literacy and predictive analytics 104 Data literacy and prescriptive analytics 108 Data literacy and the four levels of analytics - the holistic puzzle 111 Chapter summary 112 Notes 113 07 The steps of data literacy learning 115 The role of leadership and data literacy learning 116 The role of data and analytical strategy and data literacy learning 118
CONTENTS A data literacy learning framework and approach 120 Learning for the four characteristics of data literacy 125 Learning for a strong data literate culture 128 Other areas of data literacy learning and focus 131 Chapter summary 133 Notes 133 08 The three Cs of data literacy 135 The first C of data literacy: Curiosity 136 The second C of data literacy: Creativity 144 The third C of data literacy: Critical thinking 150 Reading data 152 Working with data 152 Analyzing data 153 Communicating with data 153 Chapter summary 154 Notes 155 09 Data informed decision-making 157 Steps of the data informed decision-making framework 158 Step 1: Ask 160 Step 2: Acquire 162 Step 3: Analyze 164 Step 4: Integrate 167 Step 5: Decide 171 Step 6: Iterate 173 Chapter summary and example 175 Notes 177 10 Data literacy and data and analytical strategy 179 Data driven culture 180 Business intelligence 182 Artificial intelligence 185 Machine learning and algorithms 188 Big data 190 ix
x CONTENTS Embedded analytics 191 The Cloud 193 Edge analytics 194 Geo analytics 195 Chapter summary 196 Notes 197 11 Begin your data and analytics journey 199 COVID-19 and data and analytics 200 Making a recipe 203 Focus on proactive versus reactive analytics 206 Start with the basics 208 The gamification of data and analytics 210 Find something that interests you and run to it 211 Find your why 212 Chapter summary 214 Notes 214 Index 217 |
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spelling | Morrow, Jordan Verfasser (DE-588)1251527914 aut Be data literate the data literacy skills everyone needs to succeed Jordan Morrow London ; New York, NY ; New Delhi KoganPage [2021] xiv, 223 Seiten Illustrationen, Diagramme, Karten txt rdacontent n rdamedia nc rdacarrier Literaturangaben Quantitative Methode (DE-588)4232139-6 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Quantitative Methode (DE-588)4232139-6 s Datenanalyse (DE-588)4123037-1 s DE-604 Erscheint auch als Online-Ausgabe 978-1-78966-802-5 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=032695670&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Morrow, Jordan Be data literate the data literacy skills everyone needs to succeed Quantitative Methode (DE-588)4232139-6 gnd Datenanalyse (DE-588)4123037-1 gnd |
subject_GND | (DE-588)4232139-6 (DE-588)4123037-1 |
title | Be data literate the data literacy skills everyone needs to succeed |
title_auth | Be data literate the data literacy skills everyone needs to succeed |
title_exact_search | Be data literate the data literacy skills everyone needs to succeed |
title_exact_search_txtP | Be data literate the data literacy skills everyone needs to succeed |
title_full | Be data literate the data literacy skills everyone needs to succeed Jordan Morrow |
title_fullStr | Be data literate the data literacy skills everyone needs to succeed Jordan Morrow |
title_full_unstemmed | Be data literate the data literacy skills everyone needs to succeed Jordan Morrow |
title_short | Be data literate |
title_sort | be data literate the data literacy skills everyone needs to succeed |
title_sub | the data literacy skills everyone needs to succeed |
topic | Quantitative Methode (DE-588)4232139-6 gnd Datenanalyse (DE-588)4123037-1 gnd |
topic_facet | Quantitative Methode Datenanalyse |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032695670&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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