There are two kinds of Big Data: The Big Data you have in your hands or can easily acquire and the Big Data you don't have and can't easily get your hands on.
In the former category is, for example, stock market data. At present there are roughly 6,000 traded equities and there's a wealth of data on them and all of the factors that affect them. Not only is this data wide and deep it's also, in the main, easily available. Analyzing and extracting business intelligence from this ocean of data is more-or-less straightforward (even if it gives you very little or no "edge").
Conversely, in the latter category, there's municipal bonds. These are a very different proposition with more than 1.5 million active munis at present and while basic data on them is available through resources such as CUSIPs, the actionable information required by the likes of portfolio managers to make realtime decisions is much harder to come by.
So, let's say you're a portfolio manager in New York City and in the portfolio you handle there are municipal bonds for the city of Ridgecrest, California (pop. 27,616) . News about this city will be hard to come by and you'll have to read both of the local papers (the News Review and The Daily Independent) to get solid data on which to base your buy and sell decisions.
Given you also manage perhaps a hundred or more other munis in your account, you consequently have several hundred newspapers and other data sources from all over the US that need to be scanned daily for relevant information. If you could dig int this huge mess deep enough you might notice that Ridgecrest City Council has recently voted to do something such as increase property taxes (they haven't but let's just pretend) or that a local major employer has just gone bankrupt (again, I'm just making this up) both of which will affect the price of the city's bonds.
Finding this kind of intelligence, even if it's only hours before other muni traders would know the same information, gives you an edge that could be worth hundreds of thousands of dollars. But sorting the wheat from the chaff when it comes to intelligence on munis is obviously a huge task and it's one that requires sophisticated Big Data acquisition, analysis, and organization.
This is exactly what a startup called Bitvore is doing. Bitvore's platform ingests staggering quantities of muni-related data from something like 40,000 sources including national and local newspapers, web sites, social media, and industry sources including the data on 800,0000 CUSIPs. The service then filters those data based on an ontology that recognizes 160 credit-impacting events as well as keywords defined by each user (it's a self-service model) to generate timely, relevant reports.
There is, according to Bitvore's CEO, Jeff Curie, no other BI engine like theirs that can service what he describes as the "opaque [muni] market" that's the "backwater of Wall Street." Curie says that Bitvore has found actionable muni market intelligence weeks before the regular press outlets that deal with municipal bonds cover the same news.
But servicing the muni market isn't all that Bitvore was designed for. The service can ingest any data sources and find the relevant content according to whatever the users' needs are. For example, one of their clients that is in the packaged salad business wants to improve their insight into buying trends. They existing sources were only quarterly industry association publications and Google Trends data but now, using Bitvore, they can monitor hundreds of food-related sources including restaurant menus and trend the specific ingredients they're interested in.
So, what does Bitvore cost? For the muni market it's priced at around $20,000 per seat per year which, compared to services such as Bloomberg with less specificity, is a reasonable pricing. For other markets pricing will be on application.
Bitvore has just closed its "A" series round to the tune of $4.5 million which includes nearly $1 million raised from crowdfunding sources and has, according to Curie, customers waiting to get on board. This has to be one of the most intriguing and powerful services in the real-time, Big Data, business intelligence market to emerge and will, I predict from my in-depth data, be hugely successful.