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Data Mining and Engineering in Finance

February 19-21, 2020 | UK

This marcus evans conference will drive initiatives to build an ecosystem of quality data for trade and risk, through embedding data quality efforts within the use of a central data repository, the application of synthetic and legacy data, the role and limitations of machine learning, and use of appropriate data visualisation techniques. As the volumes of data held by financial institutions increase, so too does the importance of data analytics. The role of data mining within financial institutions has seen a dramatic increase in recent years which shows signs of steadily continuing.

Spotlight

Kognitio Analytical Platform

The Kognitio In-memory Analytical Platform is an in-memory, shared nothing, massively parallel platform for large scale (big data) analytics. It allows enormously powerful data analysis platforms to be built from scalable, commodity industry standard servers. It does this by easily and efficiently harnessing very large amounts of cost effective CPU power. The Kognitio In-memory Analytical Platform is an in-memory, shared nothing, massively parallel platform for large scale (big data) analytics. It allows enormously powerful data analysis platforms to be built from scalable, commodity industry standard servers. It does this by easily and efficiently harnessing very large amounts of cost effective CPU power.


OTHER PAST CONFERENCES

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Data Reliability Engineering Conference 2021

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More Past Conferences

Spotlight

Kognitio Analytical Platform

The Kognitio In-memory Analytical Platform is an in-memory, shared nothing, massively parallel platform for large scale (big data) analytics. It allows enormously powerful data analysis platforms to be built from scalable, commodity industry standard servers. It does this by easily and efficiently harnessing very large amounts of cost effective CPU power. The Kognitio In-memory Analytical Platform is an in-memory, shared nothing, massively parallel platform for large scale (big data) analytics. It allows enormously powerful data analysis platforms to be built from scalable, commodity industry standard servers. It does this by easily and efficiently harnessing very large amounts of cost effective CPU power.

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