Business intelligence data mining
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Business intelligence data mining News
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November 12, 2020
12
Nov'20
Continuous intelligence a trend on the rise
As organizations look to gain a competitive advantage -- and many simply attempt to survive during the pandemic -- data streaming is helping them make decisions in real time.
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November 10, 2020
10
Nov'20
Presidential polling data again misses the mark in 2020
Just as they did in 2016, the election polls underestimated support for Donald Trump. Although he didn't defeat Joe Biden, the result was closer than the polls predicted.
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September 16, 2020
16
Sep'20
Miscues in 2016 inform presidential polling data in 2020
Polls and predictive analytics models are improved in 2020 after the failure to accurately predict the outcome of the 2016 election, but surprises still may loom.
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August 21, 2020
21
Aug'20
Customer location data leads to deeper level of insight
Behavioral analytics tell more about a person's true self than consumer data, according to Gravy Analytics CEO Jeff White, and are therefore key to data-driven decisions.
Business intelligence data mining Get Started
Bring yourself up to speed with our introductory content
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text mining (text analytics)
Text mining is the process of exploring and analyzing large amounts of unstructured text data aided by software that can identify concepts, patterns, topics, keywords and other attributes in the data. Continue Reading
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data mining
Data mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis. Continue Reading
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association rules
Association rules are 'if-then' statements, that help to show the probability of relationships between data items, within large data sets in various types of databases. Continue Reading
Evaluate Business intelligence data mining Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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8 top data science applications and use cases for businesses
Data scientists engage in various applications to analyze data and create technologies. These are eight common ones, with examples from different organizations and industries. Continue Reading
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How to structure and manage a data science team
Data science teams typically include various analytics and data professionals and can be set up in different ways, as explained here along with tips on managing them. Continue Reading
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14 most in-demand data science skills you need to succeed
The demand for data scientists continues to grow, but the job requires a combination of technical and soft skills. Here are 14 key skills for effective data scientists. Continue Reading
Manage Business intelligence data mining
Learn to apply best practices and optimize your operations.
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The data science process: 6 key steps on analytics applications
The data science process includes a set of steps that data scientists take to gather, prepare and analyze data and present the analytics results to business users. Continue Reading
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Data catalog best practices rely on teamwork, governance, tools
This handbook provides advice on creating data catalogs to help data analysts and other users find information in corporate systems, plus insight on data catalog trends. Continue Reading
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Data catalog management for analytics fraught with unique demands
Data catalogs for analytics applications demand detailed assessment of user needs, cross-functional teams, ready access, continuous improvement and a self-sustaining system. Continue Reading
Problem Solve Business intelligence data mining Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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Governance, compliance, ethics in data mining: Separate but equal
In the ethical mining and analysis of data, governance, compliance and ethics are mistakenly taken as one in the same. Data managers need to be aware of the critical differences. Continue Reading
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Apply data science models effectively, not just for their own sake
Having data scientists build analytical models doesn't do much for an organization if the models don't help generate business benefits. Here are some ways to make sure they do. Continue Reading
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Advanced analytics tools extract business value from big data
Big data environments based on technologies such as Hadoop and Spark are being deployed more widely -- and the same goes for advanced analytics tools that can help organizations make effective use of the data flooding into those systems. In fact, ... Continue Reading