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July 16, 2013 07:00 pm GMT
Context Relevant has raised $7 million to add to its existing $2.8 million in seed funding. In the Series A round, existing investors Madrona Venture Group and Geoff Entress were joined by Vulcan Capital, Bloomberg Beta and several other undisclosed private investors. The Seattle-based startup was founded in March 2012 and offers predictive data analysis to businesses without extensive analytics teams. Context Relevant uses real-time data from HDFS, SQL, web logs, CRM systems, market data and social media to output analyses and projections on how a business might be impacted in the future. The application also uses “behavioral libraries” which analyze interactions specifically for finance, web personalization and online travel. VP of Marketing Craig Fiebig tells me these are industries which are most interested and active in utilizing predictive data analytics. “We have a handful of people who are looking at our product in various stages of proof of value or proof of concept. We don’t have a large number of announced customers that have it deployed in production today,” Fiebig says. Interested users can sign up on the Context Relevant website for a proof-of-value deployment. The company will announce public availability later this year with the launch of its next version. Fiebig did not give specifics on upcoming improvements, but says Context Relevant is pushing the envelope on ease of use and customer adoption. Context Relevant is hoping to push past the competition by emphasizing easy accessibility and exceptional performance, but the market of big data has attracted many startups looking to provide similar services. Data analytics startup DataTorrent recently announced $8 million in funding. WibiData uses big data to predict trends and make recommendations, andclosed $15 million in Series B funding in May. It also already has several large clients under its belt, including Wikipedia and Atlassian. Another example of a startup making big data available to all organizations is SiSense, which launched in 2010 and has raised funds totaling $10 million. All these platforms are looking to serve companies with tons of data and little means of analyzing it. With useful and available data increasing at an incredible rate, these startups’ smart customers will already have a plan of how to utilize it. It’s up to companies like Context Relevant to be able to deliver on those plans.
Original Link: http://feedproxy.google.com/~r/Techcrunch/~3/LFIndyiSJ2Q/
Data Analysis Startup Context Relevant Raises $7M Series A Round
Context Relevant has raised $7 million to add to its existing $2.8 million in seed funding. In the Series A round, existing investors Madrona Venture Group and Geoff Entress were joined by Vulcan Capital, Bloomberg Beta and several other undisclosed private investors. The Seattle-based startup was founded in March 2012 and offers predictive data analysis to businesses without extensive analytics teams. Context Relevant uses real-time data from HDFS, SQL, web logs, CRM systems, market data and social media to output analyses and projections on how a business might be impacted in the future. The application also uses “behavioral libraries” which analyze interactions specifically for finance, web personalization and online travel. VP of Marketing Craig Fiebig tells me these are industries which are most interested and active in utilizing predictive data analytics. “We have a handful of people who are looking at our product in various stages of proof of value or proof of concept. We don’t have a large number of announced customers that have it deployed in production today,” Fiebig says. Interested users can sign up on the Context Relevant website for a proof-of-value deployment. The company will announce public availability later this year with the launch of its next version. Fiebig did not give specifics on upcoming improvements, but says Context Relevant is pushing the envelope on ease of use and customer adoption. Context Relevant is hoping to push past the competition by emphasizing easy accessibility and exceptional performance, but the market of big data has attracted many startups looking to provide similar services. Data analytics startup DataTorrent recently announced $8 million in funding. WibiData uses big data to predict trends and make recommendations, andclosed $15 million in Series B funding in May. It also already has several large clients under its belt, including Wikipedia and Atlassian. Another example of a startup making big data available to all organizations is SiSense, which launched in 2010 and has raised funds totaling $10 million. All these platforms are looking to serve companies with tons of data and little means of analyzing it. With useful and available data increasing at an incredible rate, these startups’ smart customers will already have a plan of how to utilize it. It’s up to companies like Context Relevant to be able to deliver on those plans.Original Link: http://feedproxy.google.com/~r/Techcrunch/~3/LFIndyiSJ2Q/
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