Remove information-management extending-data-science-skills-across-the-organization
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Generative AI use cases for the enterprise

IBM Big Data Hub

Before long, smartphones became a way of life for organizations worldwide because of all they offer for business productivity and communication. For example, organizations can use generative AI to: Quickly turn mountains of unstructured text into specific and usable document summaries, paving the way for more informed decision-making.

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

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10 DataOps Principles for Overcoming Data Engineer Burnout

DataKitchen

For several years now, the elephant in the room has been that data and analytics projects are failing. Gartner estimated that 85% of big data projects fail. Add all these facts together, and it paints a picture that something is amiss in the data world. . Data engineers end up fixing the same problem over and over.

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From principles to actions: building a holistic approach to AI governance

IBM Big Data Hub

Whether it be financial services, employee hiring, customer service management or healthcare administration, AI is increasingly powering critical workflows across all industries. This has created concerns among both private and public organizations as to whether AI is being used responsibly. The principles of AI ethics.

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CIO as enabler: Building an ecosystem of innovation partners

CIO Business Intelligence

There’s significant debate about the future of the CIO role , but one thing is clear: Digital leaders who want to be successful must look beyond the firewall and link up with an ecosystem of vendor partners, startups, and other organizations to ensure the enterprise thrives. I would say, right now, I’m a technologist last.

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The art and science of data product portfolio management

AWS Big Data

This post is the first in a series dedicated to the art and science of practical data mesh implementation (for an overview of data mesh, read the original whitepaper The data mesh shift ). Taken together, the posts in this series lay out some possible operating models for data mesh within an organization.

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Birst Smart Analytics: Using AI to Operationalize BI

Birst BI

Operationalizing BI and analytics – that is, putting the power of data in the hands of everyone across the enterprise, not just analysts and data scientists – has always been the mantra for Birst co-founder Brad Peters. That means much of the organization depends on a few experts to leverage data to make decisions.