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Transforming data into action: The business outlook for data governance

This report, developed by The Economist Intelligence Unit and sponsored by Collibra, draws on a survey of more than 500 business executives working in North America and Europe in the financial services, healthcare and life sciences, manufacturing, retail and consumer packaged goods, telecommunications and technology industries.

Additionally, we conducted in-depth interviews with corporate leaders and experts in data governance. We would like to thank the following for their insights and contribution to this research:

Transforming data into action

Find new opportunities with the Business Reality Check

To move forward in today’s business environment, you need to first know the real barriers. From finding and maintaining the right talent to ensuring the security of customer data, business leaders have to look at many potential barriers, but in some cases, a different focus may unlock opportunity.

Optimizing data in a transparent world

Transparency ranks as one of asset owners’ and asset managers’ top concerns, (1) but simply sharing more data between both sides does not always lead to better investment outcomes.

Instead, asset managers need to find a balance between fulfilling external transparency requests and protecting competitively differentiating knowledge, while asset owners need to find a balance between understanding what data they need to reach their investment and fiduciary goals and what data could lead to information overload.

Making the Most of Machine Learning: How will AI affect business process outsourcing?

Watch our video above to learn how AI will affect business processing and oursourcing from:

-Stanton Jones, Director and Principle Analyst, ISG

Making the Most of Machine Learning: How will AI change organisational culture and structure?

Watch our video above to learn how AI will change organisational culture and structure from:

-Stanton Jones, Director and Principle Analyst, ISG
-Suhir Jha, Head of Product Management Strategy, Infosys 
-Cliff Justice, Principle, Innovation & Enterprise Solutions, KPMG

Making the Most of Machine Learning: What are the advantages for business?

Watch our video above to learn about the advantages Machine Learning can offer your business from:

-Cliff Justice, Principle, Innovation & Enterprise Solutions, KPMG
-Suhir Jha, Head of Product Management Strategy, Infosys 

Making the Most of Machine Learning

Research conducted by the Economist Intelligence Unit (EIU) and written in discussion with SAP shows that many organizations are moving ahead now, some aggressively, to integrate ML into their operations. For example, the survey of 360 organizations shows that on average 68% use ML to at least some extent today to enhance their business processes.

Making the Most of Machine Learning

ML is not just a technology; it is core to the business strategies that have led to the surging value of organizations that incorporate it into their operating models—think Amazon, Uber, and Airbnb. Fast Learner organizations get that. 

Fewer Fast Learners than other organizations suffer from a lack of strategic clarity about ML. And fewer are plagued by organizational resistance to change. The reason may be that ML is viewed as more than a tactical tool for simply automating away costs and people. 

オリンピックのオッズ: 自動運転が日本の自動車大手に与えるインパクトとは?

日本政府と大手自動車メーカーは、オリンピックを非公式な期限として、次世代型の新しい 自動運転車の開発を進めている。日本が目指すのは、1964年のオリンピックにおける快挙 を再現することだ。当時、最初の高速鉄道『新幹線』が登場し、これによって、日本は輸送 のパイオニアとしての評判を確立した。 

しかし、全自動運転車の市場導入について、これよりはるかにアグレッシブな計画を発表しているグローバルな競合企業もある。中には、向こう数年のうちに主要都市の道路に登場する可能性があるものも見られる。Boston Consulting Groupでは、2035年までに、世界で販売される車の4分の1は自動運転が可能になると予想している。

日本の自動車メーカーは、現在の市場地位を保持したいのであれば急がねばならないかも しれない。 

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