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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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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

The point is that the 100% association between the event and the preceding condition has no special predictive or prescriptive power. In statistical terms, the joint probability of event Y and condition X co-occurring, designated P(X,Y), is essentially the probability P(Y) of event Y occurring. Pay attention!

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Business analytics can help you improve operational efficiency, better understand your customers, project future outcomes, glean insights to aid in decision-making, measure performance, drive growth, discover hidden trends, generate leads, and scale your business in the right direction, according to digital skills training company Simplilearn.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way.

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5 Sources of Data for Customer Analytics and Their Benefits

Smart Data Collective

There is no disputing that data analytics is a huge gamechanger for companies all over the world. Global businesses are projected to spend over $684 billion on big data by 2030. There are many ways that companies are using big data to boost their profitability. Customer Experience Analytics.

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AIOps reimagines hybrid multicloud platform operations

IBM Big Data Hub

As shown in the following diagram, an issue in the environment triggers several events across the full stack of the business solution. This results in an unmanageable event flood. Moreover, there are often duplicate events due to full-stack level observability and these events result in data silos.

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

Our Olympic Games Executive Director Christophe Dubi has a very strong belief in the notion that we can’t properly manage an Olympic event unless we can measure it.”. Athletes and sports are the heart of the Games, and the competition schedule drives everything around the event. Data will create a better-connected future.