DataSift, company that provides developers and third parties with access to Twitter, Facebook and other social data sources, is debuting new tools today to help businesses easily mine, filter and incorporate large amounts of social data into existing business and development platforms.
For background, developers, businesses, media companies and organizations use DataSift to mine the Twitter fire hose of social data, as well as Facebook, YouTube, blogs, forums and online message boards. But what makes DataSift special is that it can sort through billions of social interactions then filter this social media data for demographic information, online influence and sentiment, either positive or negative.
As we’ve reported in the past, DataSift does not limit searches based on keywords and applies natural language processing to turn unstructured data into structured, digestible information. The company’s product allows companies of any size to define extremely complex filters, including location, gender, sentiment, language, and even influence based on Klout score, to provide quick and very specific insight and analysis.
Push allows businesses to more easily integrate and analyze Social Data alongside their own business data. Using DataSift, companies can set up feeds and manage when, how and where the data will be pushed. Push integrates with existing BI applications, databases, data warehousing platforms and other cloud services, including Amazon DynamoDB, Amazon S3, MongoDB, CouchDB, FTP/SFTP, ElasticSearch and WebHooks.
DataSift’s Query Builder wants to give non-technical managers the ability to do massive data searches with complex filters. Basically the feature provides a graphical interface within DataSift to create sophisticated filters that mine the Social Web both real-time and historically without needing to learn a programming language.
DataSift is also open sourcing the Query Builder, which is written in HTML5 and Javascript, so that it may be embedded into customer products and customized.
DataSift’s Nick Halstead says the company deals with 700 million data interactions a day with over 20,000 data streams. Currently, DataSift processes two to three terabytes of data a day, and the company says that the volume of data passing through the platform has tripled over the past year.
