Big Data Related Topics 
TechCrunch
AUGUST 26, 2021
Once an organization has extracted data from their security tools, Monad’s Security Data Platform enables them to centralize that data within a data warehouse of choice, and normalize and enrich the data so that security teams have the insights they need to secure their systems and data effectively.
TechCrunch
SEPTEMBER 30, 2021
Data centers are taking on ever-more specialized chips to handle different kinds of workloads, moving away from CPUs and adopting GPUs and other kinds of accelerators to handle more complex and resource-intensive computing demands. “We were grossly oversubscribed for this round,” he said.
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TechCrunch
NOVEMBER 28, 2023
It’s a tough day for Dataminr, the New York-based big data unicorn last valued at $4.1 TechCrunch has learned that the company — which uses AI and big data algorithms to provide predictive insights about news and other global events, is laying off about 20% of staff today, or around 150 people.
TechCrunch
NOVEMBER 16, 2020
Today, a new London startup called Harbr , which has built a secure platform to enable big data exchange, is announcing a big round of funding to tap into that demand. “We’re really focused on helping people to treat data as a product. for its privacy-first, federated approach to big data analytics.
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Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.
TechCrunch
DECEMBER 14, 2020
Big data is a sham. There is just one problem with big data though: it’s honking huge. Processing petabytes of data to generate business insights is expensive and time consuming. Processing petabytes of data to generate business insights is expensive and time consuming. What should a company do?
TechCrunch
JULY 12, 2021
to bring big data intelligence to risk analysis and investigations. Quantexa’s machine learning system approaches that challenge as a classic big data problem — too much data for a human to parse on their own, but small work for AI algorithms processing huge amounts of that data for specific ends. .
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Businesses today compete on their ability to turn big data into essential business insights. To do so, modern enterprises leverage cloud data lakes as the platform used to store data for analytical purposes, combined with various compute engines for processing that data.
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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.
Speaker: Daniel O'Sullivan, Product Designer, nCino and Jeff Hudock, Senior Product Manager, nCino
We’ve all seen the increasing industry trend of artificial intelligence and big data analytics. In a world of information overload, it's more important than ever to have a dashboard that provides data that's not only interesting but actually relevant and timely.
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