Posts In Category

Data Science

While the field of data science is not tied directly to Big Data, advances in one tends to produce advances in the other. Big Data increases our ability to harvest and process data, while data science allows us to dig into it for insights.

Opinion Mining - Extraction Of Opinions From Free Text
ContributorsData ScienceMachine Learning

There’s a lot of buzz around the term “Sentiment Analysis” and the various ways of doing it. Great! So you report with reasonable accuracies what the sentiment about a particular brand or product is. Opinion Mining and Sentiment Analysis After publishing this report, your client comes back to you and

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Data Thinking Meets Data Natives – A New White Paper By *Um
Case StudiesData NativesData Science

“Data is part of our new cultural identity, transforming the way we communicate, learn and interact.” – This is the credo of the Data Natives conference, and one of the speakers at the event, Klaas Bollhoefer from The unbelievable Machine Company (*um), is taking it one step further: He adds

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Tips All Cios Should Know About Backup Reporting And Management
ContributorsData ScienceTechnology & IT

All over the world, companies are losing millions of dollars because of data loss and unexpected downtime.  This is a result of the majority of businesses being behind the times with respect to their data protection and restore plans, not to mention failed backups, and various compliance requirements being put

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Data Around The World - Part Viii: The End Of The Tour
ContributorsData ScienceTransportation & Logistics

The STORM team is back home. In 80 days, they have traveled the earth, showing that electric driving is possible – and very cool. They showed that a strong team can accomplish amazing things and change the world, by building their own bike and traveling around the world with it. Digital

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The White Rabbit, Cheshire Cat And Your Analytics Wonderland: How Data Curation Reminds Me Of A Familiar Childhood Journey
BI & AnalyticsContributorsData Science

Analysis is easy. It’s rational and straightforward. Understand the relatively linear set of steps for populating an analytic model and you’re set for success. Finding insights is the part of the data process that is hard. It requires the non-linear skill of interpretation. Interpretation is inexact, it requires judgement and

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Data Around The World - Part Vii: Hacking At Itility
ContributorsData ScienceTransportation & Logistics

The last stage of the STORM 80-day tour will be driven on November 2 – from Paris to Eindhoven, accompanied by many electrical vehicles. Hacking at ITility In the meantime, we used the results from the hackathon at Stanford University, to dig deeper into that same data set during the

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7 Signs You Should Move To Big Data Storage
Big DataContributorsData Science

Relational databases have been in place for decades, but many organizational owners as well as administrators have come across the concept of big data. Big data defies the laws of relational databases and lets you store unstructured data. Basically, you can store anything and everything. As your data requirements increase,

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3 Steps Data-Savvy Innovators Use To Retain Customers
ContributorsData ScienceMarketing & Sales

Subscription box businesses are more popular than ever, with average site visits growing by 3,000% over the past three years and revenue skyrocketing (Loot Crate, a DataScience customer, was ranked No.1 on the Inc 5000 fastest growing companies list this year with a whopping 66,789% growth in revenue since 2013).

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Mind The Gap: What Lessons Can Be Learned To Upskill The Uk’s Workforce In Data Science?
ContributorsData ScienceTechnology & IT

The recent explosion in data, connectivity and computing power – combined with powerful, new analytics tools – has sparked huge interest in data science. In response, forward-thinking businesses are looking at how they can derive insights from big data analytics to better understand their customer base and give them a

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Driving Value With Data Science
Big DataContributorsData Science

Fighting fraud, reducing customer churn, improving the bottom line –  these are just a few of the promises of data science. Today, we have more data to work with than ever before, thanks to new data-generating technologies like smart meters, vehicle telemetry, RFID, and intelligent sensors. But with all that

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