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Business intelligence data mining News
December 12, 2019
There's no such thing as a data science unicorn, U.S. government experts caution. You'll need more than programmers and technical expertise on your data science team.
October 08, 2019
GoodData partners with Amazon Web Services to allow the vendor's users to store and manage their data in Amazon Redshift, a cloud data warehouse powered by AWS.
September 24, 2019
TigerGraph, a graph database vendor, now offers a native cloud database-as-a-service product with its newest release.
August 23, 2019
With more and more museums using data to inform their decision-making processes, visitors are reaping the benefits by enjoying a better user experience.
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A data scientist is a professional responsible for collecting, analyzing and interpreting extremely large amounts of data. The data scientist role is an offshoot of several traditional technical roles, including mathematician, scientist, ... Continue Reading
Big data analytics is the often complex process of examining large and varied data sets, or big data, to uncover information -- such as hidden patterns, unknown correlations, market trends and customer preferences -- that can help organizations make... Continue Reading
This handbook examines the ethics of data mining and offers advice on missteps to avoid when mining and analyzing customer data to help drive marketing campaigns. Continue Reading
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Data modeling platforms are starting to incorporate features to automate data-handling processes, but IT must still address entity resolution, data normalization and governance. Continue Reading
The rise of augmented analytics empowers businesses to find correlations in data that might very well be the critical difference in operational efficiency and cost savings. Continue Reading
Data science and business analyst roles differ in that data scientists must deep dive into data and come up with unique business solutions -- but the distinctions don't end there. Continue Reading
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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
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
BI vendors are increasingly using NLP technology to make their products work more like a web search, with simplified user interfaces and improved ease of use for customers. Continue Reading
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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
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
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