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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

The Data Scientist profession today is often considered to be one of the most promising and lucrative. The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Previously, such problems were dealt with by specialists in mathematics and statistics.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

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Top 14 Must-Read Data Science Books You Need On Your Desk

datapine

By acquiring a deep working understanding of data science and its many business intelligence branches, you stand to gain an all-important competitive edge that will help to position your business as a leader in its field. Data science, also known as data-driven science, covers an incredibly broad spectrum.

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How Restaurant Analytics Can Make Your Business More Profitable

datapine

Exclusive Bonus Content: Ready to use data analytics in your restaurant? Get our free bite-sized summary for increasing your profits through data! A sobering statistic if ever we saw one. Data offers the power to gain an objective, accurate, and comprehensive view of your restaurant’s daily functions.

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

IBM Big Data Hub

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

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How Gilead used Amazon Redshift to quickly and cost-effectively load third-party medical claims data

AWS Big Data

They recently needed to do a monthly load of 140 TB of uncompressed healthcare claims data in under 24 hours after receiving it to provide analysts and data scientists with up-to-date information on a patient’s healthcare journey. This data volume is expected to increase monthly and is fully refreshed each month.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Many customers migrate their data warehousing workloads to Amazon Redshift and benefit from the rich capabilities it offers, such as the following: Amazon Redshift seamlessly integrates with broader data, analytics, and AI or machine learning (ML) services on AWS , enabling you to choose the right tool for the right job.