2015-07-23

Last week while in New York, DataSift announced some great new products including: VEDO Intent (active machine learning for categorization and classification) and our new PYLON Partner Portal. While we were out there we also held our first dev|datasift event in New York, a lunch and learn for folks interested in Facebook topic data, machine learning, or social data – and we packed the house! If you missed it, much of the content we discussed it…

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bradtalking

A special thank you to everyone who made it out, and to the DataSift team members who came to support our first SF dev|datasift meetup! For those that missed it, this week we had our first San Francisco meetup, at the awesome Intersection for the Arts. Our next meetup will be in New York on June 23, and we hope some of you can make it! So what’d you miss? We had tasty food, (grilled…

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dev_cover_5

Building a strong developer community is vital to the ongoing success of DataSift. Building a close relationship with our developers helps steer our product roadmap and features to help customers get the most from our platform. We’re keen to continue building our developer community and are excited to announce our first developer meetups taking place in London and San Francisco. DataSift Developer Meetups will provide the opportunity for… Helping developers learn our products in depth…

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f8

I started at DataSift a couple of months ago and have just taken my first trip to our San Francisco office. I was lucky enough when I was in town to get myself one of the hottest tickets in Silicon Valley – a place at F8, the Facebook developer conference. Enjoying the sunshine of the city’s marina and mingling with some of social tech’s finest, they weren’t the toughest two days of my career, but…

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Screen Shot 2015-03-13 at 10.51.27 AM

This week we’ve announced our partnership with Facebook to help marketers gain insights from Facebook topic data. We know that developers are as eager as marketers to learn how our this technology works. In today’s developer blog post, Richard Caudle, our platform evangelist explains how to take the CSDL for filtering data from networks such as Twitter or Tumblr, and how to apply the CSDL to Facebook topic data. This blog post discusses DataSift’s privacy-first approach,…

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app

If you’re not a programmer or wouldn’t know one end of an API from the other, then you need a simple graphical interface for writing filters and getting results. Our platform filters vast amounts of human data from dozens of sources in real-time so writing filters could be a complex programming task. However, Query Builder represents all the sources and augmentations graphically, allowing complex filters to be constructed with a few mouse clicks. To find…

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ms-files (1)

Timely, accurate and cost-effective brand monitoring is a Holy Grail for any organization. But how do you find out about the conversations happening around your brand? Where the content is being shared? By how many users? Or who your audiences are? DataSift provides a powerful means of monitoring your brand: collecting, consuming and analyzing the social data you need to underpin your decision-making. In this Brand Monitoring use case scenario, we will assume your organization…

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ms-files (4)

With the Halloween fast approaching, we wanted to share with you the biggest differences between the world’s most famous Jason – from Friday the 13th and JSON, our best friend at DataSift. Once upon a time, there were a bunch of web services that wanted to exchange data with one another. The problem was, these services were all written by different groups of developers and they did not communicate with each other about how data…

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csdl editor

From helping the UN identify what matters to spotting trends minute-to-minute, social data has proven a powerful tool to data scientists eager to understand how humans think and behave. Unfortunately, many hurdles have impeded us from putting these data science in the forefront of our research efforts. According to a recent article in the The New York Times, “Data scientists, according to interviews and expert estimates, spend from 50 percent to 80 percent of their…

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query

One of the strengths of the DataSift platform, is the ease with which filtered interactions can be sent to a variety of destinations. Google BigQuery is a good example. It takes no more than 10 minutes to configure a database in Google BigQuery, then it takes no more than 5 minutes to configure a filter in the DataSift platform which sends matching interactions straight to BigQuery. Sounds too good to be true? Register for this…

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