Making Data Work (PDF)
In this book, Edosa explores common challenges which limit the value that organisations can get from data. What makes his book unique is that he also tackles one of the unspoken barriers to data adoption-fear. Fear of the unknown, fear of the intangible,...
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In this book, Edosa explores common challenges which limit the value that organisations can get from data. What makes his book unique is that he also tackles one of the unspoken barriers to data adoption-fear. Fear of the unknown, fear of the intangible, fear of the investment needed and, yes, fear of losing your job to a machine. With his talent for distilling clarity from complexity, Edosa tackles this and many other challenges.
-Tim Carmichael, Chief Data Officer, Chalhoub Group
This book offers fresh insight about how to solve the interactional frictions that hamper the flow of data, information and knowledge across organisations. Yet, rather than being stuck with endless polarising debates such as breaking down silos, it shifts focus back towards the ultimate "to what end."
-Jacky Wright, Chief Digital Officer (CDO), Microsoft US
If you care about AI transformation, empowering people or advancing organisational success in an increasingly digital world, then you should read this book.
-Yomi Ibosiola, Chief Data and Analytics Officer, Union Bank
A retail giant already struggling due to the Covid-19 pandemic was faced with a disastrous situation when-at the end of a critical investment in an artificial intelligence project that had been meant to save money-it suddenly discovered that its implementation was likely to leave it worse off. An entire critical service stream within an insurer's production system crashed. This critical failure resulted in the detentions of fully insured motorists for allegedly not carrying required insurance.
Making Data Work details these two scenarios as well as others illustrating the consequences that arise when organizations do not know how to make data work properly. It is a journey to determine what to do to "make data work" for ourselves and for our organisations. It is a journey to discover how to bring it all together so organisations can enable digital transformation, empower people, and advance organisational success. It is the journey to a world where data and technology finally live up to the hype and deliver better human outcomes, where artificial intelligence can move us from reacting to situations to predicting future occurrences and enabling desirable possibilities.
As a global cross-industry AI and data transformation leader, Edosa Odaro has led several innovations that have resulted in organisational success thanks to the effective implementation of data transformation strategies. In leadership positions across diverse sectors, he has helped over 35 leading international organisations deliver significant impact through analytics and intelligent interventions.
A Nigerian-born data specialist with an academic background in economics, computer science, business, technology and innovation, Edosa is a firm believer in the importance of a significant focus on people and on culture as well as a brand of inclusion that is underpinned by a diversity of minds. From his vast store of meticulous field notes and interview transcripts chronicling 23 years of experience, he has compiled a record of insights and methodologies. A keen advocate for diversity and an experienced presenter and speaker, Edosa has been named a Financial Times Top 100 Most Influential Leader and one of the U.K.'s 30 Most Influential Black Leaders in FinTech. Beyond the world of work, Edosa enjoys spending time with his wife and two sons - experiencing a variety of activities, including football, cycling, running, and skiing.
- Autor: Edosa Odaro
- 2022, 1. Auflage, 220 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1000566242
- ISBN-13: 9781000566246
- Erscheinungsdatum: 03.04.2022
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 3.78 MB
- Ohne Kopierschutz
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