Big Data Related Topics 
Acuvate
NOVEMBER 23, 2020
9 Biggest Big Data Mistakes Every Company Should Avoid The success from Big Data and data analytics initiatives for a lot of traditional companies has been restricted to only small parts of their business. A huge impact through big data projects is something that not many have been able to achieve.
Jeffrey Phillips
FEBRUARY 12, 2018
Lately, with the advent of "big data", machine learning and other factors associated with data and more intelligent processes, the argument has been made that these capabilities will solve the innovation gap. To date, there's been some improvement but the innovation gap still remains.
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Yet2
FEBRUARY 7, 2024
yet2 employed their proprietary Big Data approach to quickly ingest and analyze thousands of data points across their database of 5,000+ CMOs, reducing the analysis time from months to days. yet2 ’s Big Data analysis was crucial for matching this information to the China CFDA database.
Yet2
JANUARY 9, 2023
Using Big Data in our own scouting activities has been an investment we’ve been making over the few years. To help make this intangible concept feel a little more real, below we share just 3 examples of how we at yet2 leverage Big Data in our scouting: Starting with unique, quality datasets: avoid “garbage in, garbage out.”
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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.
IdeaScale
JUNE 12, 2019
Big data has been a foundation of innovation ever since the first suggestion box was put out. Since then, the data set has only kept growing, until now you can filter thousands or even millions of data points. How do you effectively use big data to drive innovation? Collect Only Relevant Data.
Acuvate
MARCH 4, 2019
In order to understand at what point ‘data’ transitions into being ‘big data’, and what its key elements are, it is imperative that we study the 5 Vs associated with it: Velocity, Volume, Value, Variety, and Veracity. What is Big Data. Big data volume defines the ‘amount’ of data that is produced.
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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