Data stories worth sharing

data analytic

15 Reddit User and Data Analytic Tools via Quertime

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Thank you Quertime for including Import.io in your article on data analytic solutions! Read the article on Quertime    When you take data-driven decisions, they Read more

Web data extraction: Custom, commercial offerings ease the task

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In a article for TechTarget’s SearchITChannel, Moshe Kranc, chief technology officer at Ness, describes how custom and commercial offerings, bolstered by machine learning, can now facilitate Read more

Epic rain in San Jose, CA last night, or was it?

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  My CEO messaged the team from Los Gatos last night and asked, “Anyone ever seen rain as heavy as that in California before. Whoa.” Read more

Import.io in The Harvard Business Review: The Competitive Landscape for Machine Intelligence

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It’s that time of the year: about a month early, Shivon Zilis from Bloomberg Beta has just released her annual State of Machine Intelligence report Read more

Using data for product development by Steven Sinofsky (Andreessen Horowitz)

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Want to know how successful companies like Microsoft got to where they are today? By using data in smart, innovative ways. 

In this interview with Editor-in-Chief of ReadWrite, Owen Thomas, Steven Sinofsky draws on his experience at Microsoft and Andreessen Horowitz to tell you how to use data to drive product development. This fun and engaging interview will teach you how to use data, what pitfalls to be aware of and how to align customer support and product development. 

Managing ethics in the age of big data

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The Big Data revolution has raised a myriad of ethical issues related to privacy, confidentiality, transparency and identity. Who owns all that data that you’re analyzing? Are there limits to what kinds of inferences you can make, or what decisions can be made about people based on those inferences?

Navigating the fast-paced world of data isn’t easy. So it’s important that we put a good framework in place because the consequences of a slip-up can be severe.

Andrew Fryer, a Data Evangelist at Microsoft, talks you through some common ethical scenarios. He discusses good and bad usages of data, teaching you how to tell the difference. Finally, he gives you three things you should be doing to manage data ethically in your company.

5 innovative tech trends not to miss this year

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Tapping into what consumers want next is a startup founder’s Holy Grail. Being on the cusp of a budding trend is what makes the Airbnbs and Uber’s of this world so successful.

But how can you find out what the next big thing is going to be? By studying trends of course!

Head of Trends and Insights at TrendWatching, David Mattin, walks you through the latest tech trends and shows you how to interpret them. Where will you find your lightbulb moment? Watch the video to find out!

The secret ingredient for data driven decisions

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In our quest to make every business decision data-driven, getting the data is only half the battle. Next you’ve got to get people to actually use it. 

In this short video, Daniel Frank from Stripe gives away his secret ingredient for getting the team at Stripe to love quality data reporting. 

The art of hiring data scientists

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The Data Scientist is one of the most sought after positions in tech – and much of the business world. But the demand is very quickly outstripping the supply.

McKinsey estimates that by 2018, the U.S. economy will have a shortage of 140,000 to 190,000 people with analytical expertise. And if you’re a startup or business that’s looking to expand your data science operations, that might sound a little scary.

How can you attract top talent in such a competitive market?

We’re not saying it’s going to be easy, but with these tips from Data Scientist at Insightly, Sara Vera, it’s certainly going to get a lot easier.

In her keynote at Extract SF 2014, Sara gave us her top three tips for hiring great Data Scientists. And now, she’s sharing them with you! Watch the quick 10 minute video of her talk and then read on for a more in depth look at her insights.

Data scientists vs data analysts: Why the distinction matters

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s a relatively new – but already highly sought after – position, it can be hard to know where Data Analytics ends and Data Science begins. Is it science? Statistics? Programming? Analytics? Black magic? Or some strange and wonderful combination?

Luckily for us, Thomson Nguyen is here to help. In this quick 10 minute presentation, the CEO and Co-founder of Framed Data clearly outlines what makes a true Data Scientist and discusses how they differ from a traditional Analyst.