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9 Biggest Big Data Mistakes Every Company Should Avoid

Acuvate

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.

Big Data 128
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Big Data in Open Innovation

Yet2

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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Will big data solve the innovation gap?

Jeffrey Phillips

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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Propel Your Innovation Strategy into Overdrive with Big Data

IdeaScale

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.

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A Guide to Designing Delightful Dashboards

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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Understanding the 5Vs of Big Data

Acuvate

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.

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Big Data AND Consumer Anthropology

Michael Roberto

We shouldn't be choosing between leveraging big data to make decisions vs. conducting in-depth qualitiative research about our customers. As market researcher and Kellogg Professor Gina Fong states, "“Big data’s having a real moment right now. We should be using both methodologies, as they are often quite complementary.