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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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ChatGPT: le nuove sfide della strategia sui dati nell’era dell’IA generativa

CIO Business Intelligence

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

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Top 4 Business Analytics Techniques Companies Need to Adopt

TreehouseTechGroup

Most organizations start their analytics journey by asking ‘what has happened’. The business analytics technique that answers this question is called descriptive analytics as it provides a… The post Top 4 Business Analytics Techniques Companies Need to Adopt appeared first on Treehouse Tech Group.

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Five Steps for Building a Successful BI Strategy

Sisense

A business intelligence strategy is a blueprint that enables businesses to measure their performance, find competitive advantages, and use data mining and statistics to steer the business towards success. . Every company has been generating data for a while now. The question is, what are you doing with it?

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

BizAcuity

AI Adoption and Data Strategy. Lack of a solid data strategy. For the first, it is in best interest to do your own research, talk to friends, professionals and approach data services companies like ours. Data strategy allows you to build a roadmap to adopt AI. Artificial Intelligence Analytics.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Being curious about seeing something “funny” that you didn’t expect, thereby putting a “marker” in the data stream: “Look here! Cognitive analytics is basically the opposite of descriptive analytics. of organizations report having established a data-driven organization.” Pay attention! ” “91.9%

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

Sisense

“We get access, post-Games, to the ticket data to analyze any patterns in terms of incidents and responses.”. Descriptive analytics also help them understand the number of athletes and workers required to support that specific competition or sport.