Black Friday—the day after the US Thanksgiving holiday, when stores throw open their doors early to shoppers hoping to snag an incredible deal—is so-named for being the first day of the year that stores break even and their P&L starts charting out of the red and into the black. And with data revenues struggling at market data sources and distributors, the data industry may need a Black Friday-like event of its own.
Although the global economy is steadily recovering from the financial crisis, the fundamental changes it caused have made life much harder for the data industry: traders laid off during the crisis when their desks became unprofitable meant fewer subscribers to data vendors’ products; so did firms forced into bankruptcy; while those that survived through mergers and acquisitions posed another dilemma for vendors, since merged firms didn’t want to pay the same amount for data as they had previously paid separately, instead trying to consolidate contracts and usage.
Like a Black Friday bargain-hunter, these firms shopped around and haggled hard to get the best deal, knowing that vendors would offer a discount to keep business flowing. But as time goes on, it is becoming harder for vendors to keep a steady flow of new business coming through their doors, forcing them to find other ways to attract and retain clients, such as by creating more comprehensive and “stickier” services. For example, Interactive Data’s FutureSource business added trading capabilities earlier this year, and has now expanded its commodities content, while also offering more flexible options for accessing its data, to attract a broader range of potential users. Meanwhile, Asian data provider Shanghai Wind Information is also bolstering its niche commodities content by integrating livestock and agricultural data from China-America Commodity Data and Analytics.
But with all the TV commercials, junk mail and online deals, a determined shopper almost needs Big Data analytics to process all these sources to find the best deal. It’s a similar story when seeking out the best trade, where Big Data holds almost unlimited promise but is not without its share of challenges, according to this week’s Open Platform from Michael Cooper of BT, who says analytics, visualization and cloud computing will all have roles to play in successfully navigating the perils and opportunities of Big Data. And finding the best deal is only half the battle: next, you must find out who has items in stock—or, in the case of financial markets, how to quantify supply and demand in the price spread, which is what Canadian startup Level 3 Data says it can provide.
Once you’ve navigated that, you still need to navigate the inevitable queues of other savvy consumers who arrived at the same conclusion. Queuing isn’t just frustrating; if you’ve planned an optimal route for your multi-store bargain hunt, then one excessive queue can throw off your schedule, and its entire ability to achieve results. Again, the same is true in the data world, where queuing can hamper multicast data networks, and where insufficient capacity or an underperforming piece of hardware can cause applications to re-request data, clogging networks and impacting other data-consuming applications—something that Rai Technology is addressing with the latest version of its Rai Insight network monitoring tool.
So now you’re prepared to tackle Black Friday shopping, IMD-style. But by focusing on materialistic talk of Black Friday and all the things we want but don’t have, we risk forgetting the day it follows: Thanksgiving, when we give thanks for all that we do have, such as family and friends, and basic amenities such as power, water and a roof over our heads. In the aftermath of Hurricane Sandy, some still lack these. So if you’re a canny Black Friday shopper, please donate some of what you saved to the continuing relief efforts. And if we can apply the same dedication to changing the data industry—not just bargain-hunting—as we do to Black Friday shopping, then perhaps we’ll be able to give it the kick-start it needs.
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