DATA DRIVEN
MANAGEMENT
Advanced Business Management - SP
Marie Van Pelt
,
,INHOUD
Hoofdstuk 1: What – Data .............................................................................................................. 1
1. Geschiedenis van data: 1950 – vandaag ...............................................................................1
1.1. Definitie van data ............................................................................................................1
1.2. Geschiedenis van data ....................................................................................................1
1.2.1. Een aantal observaties in de geschiedenis van data ......................................................2
2. Data producers ...................................................................................................................3
2.1. Processen ......................................................................................................................3
2.2. Technologie ....................................................................................................................4
2.2.1. Sensoren ....................................................................................................................4
2.2.2. Video, audio en afbeeldingen.......................................................................................4
2.2.3. Internet ......................................................................................................................5
2.2.4. Business applications .................................................................................................6
2.3. Data in de haven van Antwerpen ......................................................................................6
3. Big Data V’s ........................................................................................................................7
4. Datatypes ...........................................................................................................................9
Hoofdstuk 2: Why – Value.............................................................................................................10
1. Value stream .................................................................................................................... 10
1.1. Value streams en data ................................................................................................... 10
2. Data use case (UC)............................................................................................................ 11
2.1. Service desk example .................................................................................................... 11
2.2. Formaat ....................................................................................................................... 11
3. Business value pyramids ................................................................................................... 12
3.1. Value pyramids ............................................................................................................. 12
3.1.1. B2C value pyramid .................................................................................................... 12
3.1.2. B2B value pyramid .................................................................................................... 13
Hoofdstuk 3: What – Data Tools ....................................................................................................14
1. Analytical tools ................................................................................................................. 14
1.1. Spreadsheets ............................................................................................................... 14
1.2. Dashboards .................................................................................................................. 14
1.3. Data science toolboxes ................................................................................................. 14
2. Digital applications............................................................................................................ 15
3. AI prompts ........................................................................................................................ 15
, Hoofdstuk 4: What – Data Products ..............................................................................................16
1. Data products ................................................................................................................... 16
2. Data products parts .......................................................................................................... 17
2.1. Dataset ........................................................................................................................ 17
2.1.1. Multi-table dataset ................................................................................................... 17
2.2. Meta data ..................................................................................................................... 18
2.3. Fysiek format ................................................................................................................ 19
2.3.1. API ........................................................................................................................... 19
3. Data product integration .................................................................................................... 19
Hoofdstuk 5: Data Transformations ..............................................................................................20
1. DIKW framework ............................................................................................................... 20
1.1. Raw data ...................................................................................................................... 21
1.2. Information................................................................................................................... 21
1.3. Knowledge.................................................................................................................... 21
1.4. Wisdom ........................................................................................................................ 21
2. Typical data transformations .............................................................................................. 22
2.1. Conversion ................................................................................................................... 22
2.2. Aggregation .................................................................................................................. 22
2.3. Filtering ........................................................................................................................ 22
2.4. Integration .................................................................................................................... 23
2.5. Advanced ..................................................................................................................... 23
Hoofdstuk 6: Data Visualisation and Storytelling...........................................................................24
1. The story of Ignaz Semmelweis........................................................................................... 24
1.1. Geleerde lessen ............................................................................................................ 25
2. Data storytelling ................................................................................................................ 25
2.1. Hoe analyse en synthese samenkomen .......................................................................... 25
2.2. Combineer data, visualisatie en verhaal ......................................................................... 26
2.3. Redenen dat het vertellen van een verhaal werkt ............................................................. 26
2.4. Het belang van een narratief .......................................................................................... 26
3. Best practices ................................................................................................................... 27
3.1. Story structure .............................................................................................................. 27
3.2. Providing context .......................................................................................................... 27
3.3. 4 D’s............................................................................................................................. 28
3.4. Using text and visual clues............................................................................................. 30
4. Article “Contextualized Insights” ........................................................................................ 30
4.1. Zes manieren om je belangrijkste inzichten te contextualiseren ....................................... 30
MANAGEMENT
Advanced Business Management - SP
Marie Van Pelt
,
,INHOUD
Hoofdstuk 1: What – Data .............................................................................................................. 1
1. Geschiedenis van data: 1950 – vandaag ...............................................................................1
1.1. Definitie van data ............................................................................................................1
1.2. Geschiedenis van data ....................................................................................................1
1.2.1. Een aantal observaties in de geschiedenis van data ......................................................2
2. Data producers ...................................................................................................................3
2.1. Processen ......................................................................................................................3
2.2. Technologie ....................................................................................................................4
2.2.1. Sensoren ....................................................................................................................4
2.2.2. Video, audio en afbeeldingen.......................................................................................4
2.2.3. Internet ......................................................................................................................5
2.2.4. Business applications .................................................................................................6
2.3. Data in de haven van Antwerpen ......................................................................................6
3. Big Data V’s ........................................................................................................................7
4. Datatypes ...........................................................................................................................9
Hoofdstuk 2: Why – Value.............................................................................................................10
1. Value stream .................................................................................................................... 10
1.1. Value streams en data ................................................................................................... 10
2. Data use case (UC)............................................................................................................ 11
2.1. Service desk example .................................................................................................... 11
2.2. Formaat ....................................................................................................................... 11
3. Business value pyramids ................................................................................................... 12
3.1. Value pyramids ............................................................................................................. 12
3.1.1. B2C value pyramid .................................................................................................... 12
3.1.2. B2B value pyramid .................................................................................................... 13
Hoofdstuk 3: What – Data Tools ....................................................................................................14
1. Analytical tools ................................................................................................................. 14
1.1. Spreadsheets ............................................................................................................... 14
1.2. Dashboards .................................................................................................................. 14
1.3. Data science toolboxes ................................................................................................. 14
2. Digital applications............................................................................................................ 15
3. AI prompts ........................................................................................................................ 15
, Hoofdstuk 4: What – Data Products ..............................................................................................16
1. Data products ................................................................................................................... 16
2. Data products parts .......................................................................................................... 17
2.1. Dataset ........................................................................................................................ 17
2.1.1. Multi-table dataset ................................................................................................... 17
2.2. Meta data ..................................................................................................................... 18
2.3. Fysiek format ................................................................................................................ 19
2.3.1. API ........................................................................................................................... 19
3. Data product integration .................................................................................................... 19
Hoofdstuk 5: Data Transformations ..............................................................................................20
1. DIKW framework ............................................................................................................... 20
1.1. Raw data ...................................................................................................................... 21
1.2. Information................................................................................................................... 21
1.3. Knowledge.................................................................................................................... 21
1.4. Wisdom ........................................................................................................................ 21
2. Typical data transformations .............................................................................................. 22
2.1. Conversion ................................................................................................................... 22
2.2. Aggregation .................................................................................................................. 22
2.3. Filtering ........................................................................................................................ 22
2.4. Integration .................................................................................................................... 23
2.5. Advanced ..................................................................................................................... 23
Hoofdstuk 6: Data Visualisation and Storytelling...........................................................................24
1. The story of Ignaz Semmelweis........................................................................................... 24
1.1. Geleerde lessen ............................................................................................................ 25
2. Data storytelling ................................................................................................................ 25
2.1. Hoe analyse en synthese samenkomen .......................................................................... 25
2.2. Combineer data, visualisatie en verhaal ......................................................................... 26
2.3. Redenen dat het vertellen van een verhaal werkt ............................................................. 26
2.4. Het belang van een narratief .......................................................................................... 26
3. Best practices ................................................................................................................... 27
3.1. Story structure .............................................................................................................. 27
3.2. Providing context .......................................................................................................... 27
3.3. 4 D’s............................................................................................................................. 28
3.4. Using text and visual clues............................................................................................. 30
4. Article “Contextualized Insights” ........................................................................................ 30
4.1. Zes manieren om je belangrijkste inzichten te contextualiseren ....................................... 30
