Today marks the 100th day of the New Year, and we’d like to take a moment to reflect on a few of the more interesting developments we’ve seen thus far in the fast-moving big data analytics arena.
We’d like to introduce you to a new member of our industry advisory council: Carl Reed, formerly managing director at global financial services company Goldman Sachs and Credit Suisse. Carl is an expert in data discovery and analytics for financial institutions, and recently participated in our Tweet Chat earlier this month on “An Insider’s View: Finding Value with Data Engineering & Semantic Standards in Finance.”
The financial industry is facing a perfect storm of disruptive drivers for data management. While regulators seek accuracy and transparency, institutions are struggling with fragmented data and IT infrastructures. The path forward is “data engineering” – applying consistent semantics with scalable infrastructure to harmonize data and enable traceable and dynamic analytics.
Cambridge Semantics recently hosted a Tweet Chat with industry professionals, media and analysts to discuss Big Data in the Financial Industry using the hashtag #SmartDataChat.
Summarizing the lessons she learned from her tenure in a speech earlier this month, Mary Jo White, outgoing chair of the U.S. Securities and Exchange Commission (SEC), made a convincing case that the use of data analytics has greatly contributed to a dramatic rise in successful SEC investigations of insider trading and other securities fraud.
Data lakes are quickly becoming a hot topic as enterprises determine how best to organize and access the large volume of data they have been generating. Data Lakes are attractive for several reasons, including their ability to expand data across the enterprise while maintaining trust and security with data governance.
We are at an inflection point in the financial services industry. The evolving and overwhelming demands of regulatory compliance have forced organizations to acknowledge the need for data governance and most are developing their strategy.
State Street Bank, The EDM Council, Dun & Bradstreet, Wells Fargo and Cambridge Semantics completed an engagement to harmonize State Street's Interest Rate Swap data with Dun & Bradstreet's entity hierarchy data using the Financial Industry Business Ontology (FIBO) and Cambridge Semantics' Anzo Smart Data Lake®.
Unstructured data is all around us: in news stories, web pages, journal articles, social media posts, patents, research reports, presentations, and a variety of other sources. These items are unstructured in that they don’t start out with a predefined, explicit schema or structure. Historically, these documents have been read by humans looking to find information relevant to their particular tasks or roles. In today's deluge, however, the need for scalable reading, repeatability, traceability, and speed has driven the advent of text analytics platforms.
Mike Atkin of the EDM Council speaks eloquently about the "perfect storm" for data in Financial Services. Two converging forces, regulatory reporting requirements and the need for customer insight, are placing unprecedented demands on the data infrastructure in most financial institutions.