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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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11 dark secrets of data management

CIO Business Intelligence

Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

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15 Best Data Analysis Tools You Can’t Miss in 2022

FineReport

Most data analysts are very familiar with Excel because of its simple operation and powerful data collection, storage, and analysis. Key features: Excel has basic features such as data calculation which is suitable for simple data analysis. Price: Excel is not a free tool. RapidMiner. From RapidMiner. From KNIME.

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Themes and Conferences per Pacoid, Episode 7

Domino Data Lab

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

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On procedural and declarative programming in MapReduce

The Unofficial Google Data Science Blog

Sawzall is a programming language developed at Google for performing aggregation over the result of complex operations on structured data. While use of Sawzall at Google is in decline today, we believe the lessons discussed here have survived the test of time and are employed by descendant systems used throughout Google.

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Deep automation in machine learning

O'Reilly on Data

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.