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This book offers insights into how both private and public organisations can innovate and keep up with growing data volumes and increasing technological developments in the short, mid and long term.
This book offers insights into how both private and public organisations can innovate and keep up with growing data volumes and increasing technological developments in the short, mid and long term.
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Autorenporträt
Erik Beulen is a professor of Information Management at The University of Manchester/AMBS - UK. He is also a professor of Information Management & Digital Transformations at Tilburg University - NL and the academic director of the executive MSc Information Management & Digital Transformations at TIAS Business School (NL). Erik is also an external advisor at Bain & Company.
Marla A. Dans is Head of Data Management and Governance at Chicago Trading Company (CTC) - United States. Prior to CTC, Marla was Head of Data Governance at Tradeweb, consulted for data programs across multiple financial services firms, held a strategic position in JP Morgan Asset Management's chief data office, and for nearly two decades worked for Morgan Stanley in executive director roles in information technology, across application development, DevOps, infrastructure, and information security roles.
Inhaltsangabe
Part 1: Business context 1. Digital transformations explained 2. Data analytics trends clarified Part 2: Data analytics foundation 3. Data-driven decision-making 4. Monetization of data & data analytics 5. Data quality - data management in action 6. Data governance - business and IT collaboration 7. Data compliance, privacy and ethics Part 3: Digital transformation phase powered by data analytics 8. Digital 1.0 - Supplementing the going concern with digital initiatives 9. Digital 2.0 - Siloed digital to integrated digital 10. Digital 3.0: Preparing for digital transformation 2025 Part 4: Data sharing-centric digital transformations 11. Data management and governance implications of data sharing 12. Data sharing - Competitive and sustainability, compliance, privacy, and ethical implications 13. Partnering in ecosystems - How to structure collaboration? Part 5: Aligning at the crossroads of data analytics and digital transformations 14. Identifying good practices and roadmaps for aligning analytics and digital organizational goals 15. 2030 Perspective on leveraging data analytics in achieving digital transformation success
Part 1: Business context 1. Digital transformations explained 2. Data analytics trends clarified Part 2: Data analytics foundation 3. Data-driven decision-making 4. Monetization of data & data analytics 5. Data quality - data management in action 6. Data governance - business and IT collaboration 7. Data compliance, privacy and ethics Part 3: Digital transformation phase powered by data analytics 8. Digital 1.0 - Supplementing the going concern with digital initiatives 9. Digital 2.0 - Siloed digital to integrated digital 10. Digital 3.0: Preparing for digital transformation 2025 Part 4: Data sharing-centric digital transformations 11. Data management and governance implications of data sharing 12. Data sharing - Competitive and sustainability, compliance, privacy, and ethical implications 13. Partnering in ecosystems - How to structure collaboration? Part 5: Aligning at the crossroads of data analytics and digital transformations 14. Identifying good practices and roadmaps for aligning analytics and digital organizational goals 15. 2030 Perspective on leveraging data analytics in achieving digital transformation success
Part 1: Business context 1. Digital transformations explained 2. Data analytics trends clarified Part 2: Data analytics foundation 3. Data-driven decision-making 4. Monetization of data & data analytics 5. Data quality - data management in action 6. Data governance - business and IT collaboration 7. Data compliance, privacy and ethics Part 3: Digital transformation phase powered by data analytics 8. Digital 1.0 - Supplementing the going concern with digital initiatives 9. Digital 2.0 - Siloed digital to integrated digital 10. Digital 3.0: Preparing for digital transformation 2025 Part 4: Data sharing-centric digital transformations 11. Data management and governance implications of data sharing 12. Data sharing - Competitive and sustainability, compliance, privacy, and ethical implications 13. Partnering in ecosystems - How to structure collaboration? Part 5: Aligning at the crossroads of data analytics and digital transformations 14. Identifying good practices and roadmaps for aligning analytics and digital organizational goals 15. 2030 Perspective on leveraging data analytics in achieving digital transformation success
Part 1: Business context 1. Digital transformations explained 2. Data analytics trends clarified Part 2: Data analytics foundation 3. Data-driven decision-making 4. Monetization of data & data analytics 5. Data quality - data management in action 6. Data governance - business and IT collaboration 7. Data compliance, privacy and ethics Part 3: Digital transformation phase powered by data analytics 8. Digital 1.0 - Supplementing the going concern with digital initiatives 9. Digital 2.0 - Siloed digital to integrated digital 10. Digital 3.0: Preparing for digital transformation 2025 Part 4: Data sharing-centric digital transformations 11. Data management and governance implications of data sharing 12. Data sharing - Competitive and sustainability, compliance, privacy, and ethical implications 13. Partnering in ecosystems - How to structure collaboration? Part 5: Aligning at the crossroads of data analytics and digital transformations 14. Identifying good practices and roadmaps for aligning analytics and digital organizational goals 15. 2030 Perspective on leveraging data analytics in achieving digital transformation success
Rezensionen
"The best books about digital transformation combine a practitioner's experience together with original insight. Beulen and Dans have provided genuine insight based on strong fundamentals.
They understand and describe the need for an enhanced architecture function, the importance of data quality and how data ownership principles must be applied before significant strides can be made in analysis and enable implementation of AI capabilities.
As a Chief Data Officer this is a must-read, including interviews with top industry experts like Julia Bardmesser, the topics covered range from ethical considerations for data usage through to adoption of advanced technologies in service of a data-first organization." Andrew Foster, Chief Data Officer, M&T Bank and lead contributor to EDM Council's Cloud Data Managment Capabilities standard (CDMC)
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