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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.

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Prescriptive Analytics – a Winning Bet for Casinos

BizAcuity

Ever since the digitization of casinos, casino managers are being exposed to a great deal of data. Hidden tangled within this sea of data lie many insights, which can open up new opportunities for growth and revenue. This is what makes the casino industry a great use case for prescriptive analytics technologies and applications.

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Prescriptive Analytics – a Winning Bet for Casinos

BizAcuity

Ever since the digitization of casinos, casino managers are being exposed to a great deal of data. Hidden tangled within this sea of data lie many insights, which can open up new opportunities for growth and revenue. This is what makes the casino industry a great use case for prescriptive analytics technologies and applications.

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The Role Of Technology In A Changing Financial Services Sector Part II

Cloudera

Thank you for joining us for part two of our discussion around data, analytics and machine learning within the Financial Service Sector Dr. Harmon. One of the key takeaways from recent times that should be considered into the future, is that banks need to rethink how they look at tail risk or extreme events that rarely happen. .

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

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What Leaders Want: Shifting to AI-Driven Healthcare

DataRobot Blog

The main themes emerging from our conversations cover data integration, security and humility, strategy, and workforce development: Join siloed data together to create longitudinal, ready-to-analyze datasets. Secure data sharing and AI humility is a necessity.

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Four starting points to transform your organization into a data-driven enterprise

IBM Big Data Hub

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. Furthermore, a global effort to create new data privacy laws, and the increased attention on biases in AI models, has resulted in convoluted business processes for getting data to users. Data governance.