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Your marketing campaign is about to launch and you need to track the response. Not just on Twitter or Facebook but across all the networks, all languages, and the long-form content such as blogs and discussion boards. You know that DataSift aggregates all these sources so you can write one simple filter. You know we have one simple API to hit for the filtered interactions, but where’s your developer gone? The last time you did…

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Pulling the Data Out of DataSift

Paul Smart 5th November 2014 1 Comment

If you’ve read my previous blogs, you’ll know that our platform allows you to filter vast amounts of real-time data. You end up with all the interactions you’re interested in – but how do you get those interactions from our platform to your app or analytics tool? There are three ways: 1. Stream them from our platform in real time 2. Have our platform send them to a destination of your choice 3. Pull them…

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When we talk about Big Data, we’re not talking about a few petabytes of structured data which has been captured, tamed and sits caged in a database waiting to be queried. We work with Big Data in the wild. Untamed, unpredictable and unbelievably big. We have close to 30 data sources hurling vast quantities of unstructured data into our platform. Then we use 10 augmentations to add more metadata to every interaction. Then, as if…

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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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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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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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We run free workshops every Thursday and I’d like to give you an example of what we cover. I’m going to use ‘Configuring Streams with CSDL in the API’ as an example, but don’t be put off if you’re a novice. We have workshops that cover the absolute fundamentals of the platform right up to advanced workshops covering complex destinations and filter optimization. The Workshop All workshops are delivered remotely by an experienced DataSift instructor….

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With any new platform or service, it can be hard to know where to start. We have hundreds of pages of documentation, but sometimes you just want someone to explain it to you. That’s why we run free workshops every week where you can be led through everything from the platform basics to some of the more advanced features. Each workshop is hosted by an experienced DataSift instructor and provides the opportunity for you to…

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