The Bloomberg article, "Big Data Is a Big Mess for Hedge Funds Hunting for Trade Signals", discusses the value of Big Data in the pursuit of generating top and bottom-line growth and growing assets under management. One of the article's heavily emphasized points is the current discrepancy in perceivable value between Big Data itself (valued greatly) and the data scientists that spent hours cleaning and analyzing data for the benefits of a firm's traders (undervalued and misrepresented in terms of corporate value).
As I've mentioned in a previous post, Big Data is vast and provides the asset-management industry with another tool to use in their research and trade decisions. However, it's only useful if someone with the appropriate statistical, mathematical, and analytical acumen spends the time to clean that data and arrives at a telling conclusion--if there even is one. Their contributions to investment firms that employ them are invaluable and yet they are offered very little "say" at the corporate roundtable.
Asset-managers looking to successfully deploy data-mining practices as part of their firms overall investment strategy need to include data-scientists in their investment and management-level discussions, not just relegate them to the back-office operations team. Considering how new and continuously-developing the world of Big Data actually is, data scientists possess the ability to convey these developments to portfolio managers and traditional equity and credit analysts, but only if they are granted the opportunity.
Yes, one could argue that personalities between traditional finance-types and scientists could clash (a la The Big Short), and firms are afraid of changing how they arrange their management in fear of backlash. But communication and interpretation is half the battle of applying Big Data to investment decisions; the other half is finding the right data to leverage, if it exists. So, firms should adjust for what they can control and bring their "quants" into more substantive corporate roles. That decision will pay dividends both in terms of corporate culture and efficacy of research methodologies.