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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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The Third Modern Data Management Summit: Making Data Work!

Reltio

The third Modern Data Management annual summit ( #DataDriven19 ) held on February 26-27 2019 attracted more than 400 business and IT professionals getting together in San Francisco to witness the future of data management, share success stories and learn best practices. Reltio was the Diamond sponsor and host of the event.

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Synthetic data generation: Building trust by ensuring privacy and quality

IBM Big Data Hub

Structured synthetic data types are quantitative and includes tabular data, such as numbers or values, while unstructured synthetic data types are qualitative and includes text, images, and video. You can combine this data with real datasets to improve AI model training and predictive accuracy.

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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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Creating and nourishing a DevOps culture: key takeaways for agencies

CGI

Digital transformation is forcing a rethinking of business process simplification, data science is taking on a new importance with a push for data-driven insights, and federal CIOs are learning how to wield new authorities effectively to meet the accompanying new levels of accountability. ravi.kumarv@cgi.com. Add new comment.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

Other potential areas : Video generation (36%) and 3D model generation (26%) can create marketing materials, virtual renderings and product mockups. Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. The skills gap in gen AI development is a significant hurdle.

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#DataDriven19 – The Fastest Way to Learn Modern MDM & Personalized Customer 360

Reltio

This year’s theme “ Organize Master Data. Personalize Customer 360 ” will cover the hottest topics relevant to master data management and customer 360, big data analytics, data science and business facing data-driven applications. what to expect: Watch quick video from last year summit.

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