Data Management: a gentle introduction. Bas van Gils

Data Management: a gentle introduction - Bas van Gils


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href="#litres_trial_promo">26.1 People first, and the need for training

       26.2 Types of training

       26.3 How to design a training program

       27 SETTING UP A DATA MANAGEMENT POLICY

       27.1 Data management policy

       27.2 Typical structure for a data management policy

       27.3 Setting up a data management policy

       27.3.1 Top-down

       27.3.2 Bottom-up

       27.4 Recommendations

       28 BUSINESS CONCEPTS AND THE CONCEPTUAL DATA MODEL

       28.1 Freezing language

       28.2 Definitions and conceptual data models

       28.3 Definitions in a context

       28.4 Recommendations

       29 SETTING UP A METADATA REPOSITORY

       29.1 The importance of metadata

       29.2 Metadata repository architectures

       29.3 Implementation strategies

       29.3.1 Top-down metadata strategy

       29.3.2 Bottom-up metadata strategy

       29.3.3 Matching the strategy to the situation

       29.4 Recommendations

       30 LEVERAGING ENTERPRISE ARCHITECTURE

       30.1 EA as a source of information

       30.2 EA models and visualizations

       30.3 Building effective solutions

       30.4 Recommendations

       31 INTEGRATION ARCHITECTURE

       31.1 Data is everywhere

       31.2 Start simple

       31.3 Keep it simple

       31.4 Recommendations

       32 A PRAGMATIC APPROACH TO DATA SECURITY

       32.1 Motivation for a security framework

       32.2 Security use cases

       32.3 Security levels in business terms

       32.4 The link to security measures and controls

       32.5 Tying it together

       33 ROLES IN DATA MANAGEMENT

       33.1 Change and run

       33.2 Roles in the DMBOK

       33.3 Skills in the SFIA framework

       33.4 Definition of roles

       33.4.1 Architect

       33.4.2 Business management

       33.4.3 Data owner, data steward

       33.4.4 Project management

       33.4.5 Chief data officer

       33.4.6 Business analyst, process analyst, and system analyst

       33.5 Reflection and recommendation

       34 WORKING WITH BIG DATA

       34.1 Observations about big data adoption

       34.2 Building a culture of innovation

       34.3 Linking to data management defense

       34.4 The future of big data

       35 BUILDING A DATA MANAGEMENT ROADMAP

       35.1 To roadmap or not to roadmap

       35.2 The steps towards an effective roadmap

       35.3 Techniques

       35.3.1 Vision phase

       35.3.2 Analysis phase

       35.3.3 Portfolio phase


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