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Don’t Fear Artificial Intelligence; Embrace it Through Data Governance

CIO Business Intelligence

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation.

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Bringing an AI Product to Market

O'Reilly on Data

In this article, we turn our attention to the process itself: how do you bring a product to market? The development phases for an AI project map nearly 1:1 to the AI Product Pipeline we described in the second article of this series. The final article in this series will be devoted to debugging.). Identifying the problem.

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5 Ways Data Engineers Can Support Data Governance

Alation

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. This article will focus on how data engineers can improve their approach to data governance.

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Breaking State and Local Data Silos with Modern Data Architectures

Cloudera

But while state and local governments seek to improve policies, decision making, and the services constituents rely upon, data silos create accessibility and sharing challenges that hinder public sector agencies from transforming their data into a strategic asset and leveraging it for the common good. . Towards Data Science ).

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Data Science, Past & Future

Domino Data Lab

Greg Linden ‘s article about splitting the website on Amazon. My colleague, Ben Lorica at O’Reilly, he and I did three large surveys about adoption for ABC, that’s AI, Big Data, and Cloud in enterprise. We have an article on this on Domino. One is data quality, cleaning up data, the lack of labelled data.

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Source: [link] I will finish with three quotes.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

Experts say that BI and data analytics makes the decision-making process 5x times faster for businesses. Renowned author Bernard Marr wrote an insightful article about Shell’s journey to become a fully data-driven company. Let’s look at our first use case.