Remove Data Strategy Remove Forecasting Remove Prescriptive Analytics Remove Technology
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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. How do predictive and prescriptive analytics fit into this statistical framework?

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

With its vast assortment of sensors and streams of data that yield digital insights in situ in almost any situation, the IoT / IIoT market has a projected market valuation of $1.5 trillion by 2030. RFID), inventory monitoring (SKU / UPC tracking). RFID), inventory monitoring (SKU / UPC tracking).

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

How effectively and efficiently an organization can conduct data analytics is determined by its data strategy and data architecture , which allows an organization, its users and its applications to access different types of data regardless of where that data resides.

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Incorporating Artificial Intelligence for Businesses : The Modern Approach to Data Analytics

BizAcuity

The widespread adoption of AI technology is fueled by 3 major challenges that businesses have been facing since the last decade. AI Adoption and Data Strategy. Lack of a solid data strategy. Data strategy allows you to build a roadmap to adopt AI. AI for Business. Uncertain economic conditions.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

The company’s orthodontics business, for instance, makes heavy use of image processing to the point that unstructured data is growing at a pace of roughly 20% to 25% per month. Advances in imaging technology present Straumann Group with the opportunity to provide its customers with new capabilities to offer their clients.

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A Guide to Data Analytics in the Travel Industry

Alation

As an industry with tight margins, travel and tourism companies can use analytics to detect trends that help them reduce costs, decide future product and service offerings, and develop successful business strategies. What’s more, many companies struggle with rigid legacy technologies that increase the risk of a data breach.