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Mastering the Art of Cloud Tagging Using Data Science

Dark Reading

Cloud tagging, the process of labeling cloud assets by certain attributes or operational values, can unlock behavioral insights to optimize and automate cyber asset management at scale.

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Benefits of using Collibra with Databricks on Google Cloud

Collibra

This jointly developed service brings together data engineering, data science, analytics and machine learning through an open lakehouse platform. With an open data and cloud platform, users need data governance to continue to reap the benefits of the open architecture. Collibra offers: .

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10 everyday machine learning use cases

IBM Big Data Hub

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Part-of-speech (POS) tagging: POS tagging facilitates semantic analysis by assigning grammatical tags to words (e.g., What is text mining? noun, verb, adjective, etc.),

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Four use cases defining the new wave of data management

IBM Big Data Hub

As discussed in the previous section data virtualization and data cataloging help get the right data to the right people by making it easier to find the data that best fits their needs and access it. Automated metadata generation is essential in order to turn a manual process into one that is better controlled.

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How to achieve enterprise-scale data reliability

Collibra

As a result, organizations lack an enterprise data quality foundation to respond to regulatory, analytics, and AI demands in a scalable and cost-efficient way. Making sure data is of a high quality involves rules. An intelligent data quality system can evolve rules on-the-fly. Lots and lots of rules.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While cost wasn’t the primary driver, it reflects a growing belief that the value generated by gen AI outweighs the price tag. Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. 46% of survey respondents in 2024 showed a preference for open source models.