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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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How Data Analytics Tools Eliminate Business Owner Headaches

Smart Data Collective

One study found that 77% of small businesses don’t even have a big data strategy. If your company lacks a big data strategy, then you need to start developing one today. The best thing that you can do is find some data analytics tools to solve your most pressing challenges. Creating predictive models.

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Solving the Data Daze – Analytics at the Speed of Business Questions

Rocket-Powered Data Science

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 167
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AI In Analytics: Today and Tomorrow!

Smarten

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

The counterexample to the supervised learning explanation of precursor analytics is a “black swan” event – a rare high-impact event that is difficult to predict under normal circumstances – such as the global pandemic, which led to the failure of many predictive models in business. ” “Just 26.5%

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2020 Data Impact Award Winner Spotlight: Globe Telecom

Cloudera

Entrants in this award category are so important to recognize because of how they tie every piece of their data strategy together. And in so doing, enrich the organization and secure, report, serve and predict on all the data they have access to. . This is why Globe Telecom established the Enterprise Data Office (EDO).