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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?

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Fear has Replaced Apathy as the Number One Enemy of Data

Jim Harris

Background: “Apathy is the enemy of data quality”. I began work on data quality in the late 1980s at the great Bell Laboratories. Indeed, I can’t recall a single person who claimed high-quality data wasn’t important. As my interests expanded beyond quality, I expanded the scope of my scan to all things data.

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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

The Semantic Web, both as a research field and a technology stack, is seeing mainstream industry interest, especially with the knowledge graph concept emerging as a pillar for data well and efficiently managed. And what are the commercial implications of semantic technologies for enterprise data? Source: tag.ontotext.com.

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A CDO’s Guide to the Data Catalog

Alation

In 2002, Capital One became the first company to appoint a Chief Data Officer (CDO). Early CDOs largely sought to ensure compliance with regulations around financial data, taking a defensive posture to guard company and customer information. Today, the modern CDO drives the data strategy for the entire organization.

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Why Data Driven Decision Making is Your Path To Business Success

datapine

The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason. By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward.

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Data Science Challenges – It’s Deja Vu all over again!

Peter James Thomas

Based on Kaggle’s State of Data Science Survey 2017 (Sample size: 10,153). The text in the above exhibit is not that clear [2] , so here are the 20 top challenges [3] faced by those running Data Science teams in human-readable form: #. Dirty Data. Lack of Data Science talent in the organization. Privacy issues.