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In an article titled “Watch how word of Ebola exploded in America” Time.com last week published data showing how 10.5 million tweets referenced Ebola between September 16 and October 6. Predictably there has been a massive surge in the conversation since the first Ebola diagnosis inside the USA on September 30. The article features a graph from @twitterReverb which captures this surge brilliantly, but also highlights some of the limitations of relying solely on traditional…

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In the last seven years, we’ve been having an incredible run at DataSift. Working with more than 1,000 customers in 40 countries and enjoying explosive growth. Since I founded the company, we’ve seen the team expand from humble beginnings in Reading, UK to a global operation with more than 120 employees spread across the US, Canada and the UK. DataSift is on a roll and poised to take an even bigger leap in 2015. With…

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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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During the past decade, few business buzzwords/terms have had as much success as ‘Big Data’. It’s graced the covers of business magazines, been the central topic of an endless number of conferences, and helped countless tech folks explain to their families what they do for a living. In this blog post I’d like to propose a new way at looking at ‘Big Data’ given the changing nature of data in organizations that addresses an inherent…

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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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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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Big data isn’t just about petabytes and NoSQL. The ability to sift through billions of records gives us a newfound ability to listen and get a pulse of any situation, even in real time. With better data, we can make more impactful decisions in less time. Our data partner Lexis Nexis has put these listening capabilities to solve a devastating global problem — human trafficking. In their collaboration with STOP THE TRAFFIK, Lexis Nexis went…

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For a textbook example of how DataSift is helping partners aggregate, process and deliver social data—read on. Onalytica’s solutions surface relevant influencers for their clients, helping them to manage those relationships over time. Working with DataSift, Onalytica generated cost savings through less reliance on an internal data center, and eliminated data gaps for an enhanced end-user experience. So what’s behind this partnership success? Onalytica helps leading brands and agencies systematically manage their relationships with influential…

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Today, we’re kicking off a new series of blog posts under the umbrella of ‘getting back to basics on data’. We want to tackle the most fundamental questions around data, in particular human-generated or as we like to call it – Human Data. What is it, what do you need to be able to work with it, what value can you extract from it and many more. First up – unstructured data. It’s an important…

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When handling huge amounts of human generated data, filtering isn’t only useful – it’s essential. But filtering only takes you so far. Depending on your filters, you may have anywhere from a few thousand to a few million filtered interactions sitting in your destination. Which are the most important? How can you classify them into groups? What kind of system will you need to do the classification? This is happening in real-time, can you classify…

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