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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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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

How to make smarter data-driven decisions at scale : [link]. The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. A lot has changed in those five years, and so has the data landscape. But if they wait another three years, they will never catch up.”

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Five Steps for Building a Successful BI Strategy

Sisense

And every business – regardless of the industry, product, or service – should have a data analytics tool driving their business. Every business needs a business intelligence strategy to take it forward. . The BI strategy played a major role in the setup, execution, and ongoing implementation of the BI platform.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. To do this at scale, you have to use AI/ML services for decision-making.

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

BizAcuity

Combined, it has come to a point where data analytics is your safety net first, and business driver second. AI Adoption and Data Strategy. Lack of a solid data strategy. In order to adopt AI solutions for your business, the best way forward is to first ensure that you have a strong data strategy in place.

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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. Why is data analytics important for travel organizations? Travel can be stressful and emotionally fraught.

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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?