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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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Disrupt and Innovate in a Data-Driven World

Cloudera

If you do an internet search for ‘data-driven disruption’ you can find articles about almost every industry being disrupted by digitalisation and new applications of data. While there are instances of data-driven efforts in the nonprofit sector, they are not as widespread as they can be.

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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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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

As the world becomes increasingly digitized, the amount of data being generated on a daily basis is growing at an unprecedented rate. This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. What is Big Data? What is Big Data?