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7 sins of digital transformation

CIO Business Intelligence

As CIOs prepare for the next wave of digital transformation, they must demonstrate shorter-term business impacts from technology investments and achieve larger innovation goals that evolve the organization’s business model.

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3 key digital transformation priorities for 2024

CIO Business Intelligence

The analyst reports tell CIOs that generative AI should occupy the top slot on their digital transformation priorities in the coming year. I wrote in Driving Digital , “Digital transformation is not just about technology and its implementation. Luckily, many are expanding budgets to do so. “94%

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What is the most important question for Data Science (and Digital Transformation)

KDnuggets

While machine learning offers significant power in driving digital transformations, a business must start with the right questions and leave the math to the development teams.

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What a quarter century of digital transformation at PayPal looks like

CIO Business Intelligence

Ultimately, the goal is to drive the inclusion, ubiquity and utility of digital assets to further define the future of commerce and value exchange. Artificial Intelligence, Digital Transformation, Emerging Technology, Innovation, Payment Systems

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Why is Data Management so Important to Data Science?

KDnuggets

High data availability may help power digital transformation, but data management systems are needed to keep that data organizaed and make it accessible. Read this article to see why data management is important to data science.

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The Failed Promises of Digital Transformation and What to Do About It

Ontotext

Digital Transformation, which has been a top priority for CEOs and boards of directors for many years, has had mixed results. As graph data platforms become more widely understood, they play a key enabling role in delivering on many of the failed promises of Digital Transformation. Let’s be frank.

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Complete Guide to run Machine learning on Spark using Spark MLLIB

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The digital transformation has given rise to the release of massive amounts of data each second, and companies’ servers are not that powerful to bear the load.