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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

How to make smarter data-driven decisions at scale : [link]. The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. A lot has changed in those five years, and so has the data landscape. But if they wait another three years, they will never catch up.”

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Creating Data Value With a Decentralized Data Strategy

CIO Business Intelligence

For decades organizations chased the Holy Grail of a centralized data warehouse/lake strategy to support business intelligence and advanced analytics. billion connected Internet of Things (IoT) devices by 2025, generating almost 80 billion zettabytes of data at the edge.

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It’s not your data. It’s how you use it. Unlock the power of data & build foundations of a data driven organisation

CIO Business Intelligence

Data has always been fundamental to business, but as organisations continue to move to Cloud based environments coupled with advances in technology like streaming and real-time analytics, building a data driven business is one of the keys to success. There are many attributes a data-driven organisation possesses.

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The CDO Imperative: From Process Centric to data-driven

Alation

Data: Fertilizer for Innovation. Data helps with both of these challenges. Data helps with both of these challenges. Data is the mechanism for resolving questions. In a data-driven organization, ideas and solutions can come from anywhere. The Role of the Chief Data Officer (CDO).

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

In the world of data there are other types of nuanced applications of business analytics that are also actionable – perhaps these are not too different from predictive and prescriptive, but their significance, value, and implementation can be explained and justified differently. This is predictive power discovery.

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Achieving Trusted AI in Manufacturing

Cloudera

With the ability of manufacturers to store a huge volume of historical data, AI can be applied in general business areas of any industry, like developing recommendations for marketing, supply chain optimization, and new product development. With AI, it can even prescribe the appropriate action that needs to be taken and when.