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New book provides an accessible and practical introduction to data science

CILIP

New book provides an accessible and practical introduction to data science. Facet Publishing announce the publication of Practical Data Science for Information Professionals by David Stuart. David Stuart said of the text: "The growing importance of data science in the world today is impossible to miss ?

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MLOps and the evolution of data science

IBM Big Data Hub

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. How MLOps will be used within the organization.

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Part 1: OMG! Not another digital transformation article! Is it about understanding the business drivers?

ARMA International

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. Information and data are synonyms but have different definitions. ARMA defines data as “Any symbols or characters that represent raw facts or figures and form the basis of information” (ARMA 2016, p 12).

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A brief history of data and how it helped change the world

Collibra

Yes, the ancient pyramids relied not only on labor and raw materials, but on data collection and analysis. . Data collection is what we do. Today, we think of Big Data as a modern concept. Cloud storage, text mining and social network analytics are vital 21 st century tools. Around 300 B.C.E.,

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How to choose the best AI platform

IBM Big Data Hub

AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages. Visual modeling: Combine visual data science with open source libraries and notebook-based interfaces on a unified data and AI studio.

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Introducing watsonx: The future of AI for business

IBM Big Data Hub

In a prompt lab, users can experiment with models by entering prompts for a wide range of tasks such as summarizing transcripts or performing sentiment analysis on a document. Developers can build workflows directly in our ModelOps environment using APIs, SDKs, and libraries, managing machine learning models from development to deployment.

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What’s your data democratization strategy? How to successfully democratize data

Collibra

Read articles and reports by data experts ( Gartner and the Collibra Resource Library are both great places to start). Ask around your organization to get a feel for how and why your company is already using data, and identify ways in which data democratization could optimize every department or line of business.