Earlier this month, the Cambridge Semantics team set off for Grapevine, Texas, for the Gartner Data & Analytics Summit 2017 to join more than 3,000 big data industry customers, Gartner analysts and solution providers in the continuing discussion on driving business intelligence and analytics forward.
“If you know the enemy and know yourself, you need not fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.” - Sun Tzu
Most Competitive Intelligence (CI) and Business Strategy practitioners are likely to have come across this immortal advice from Sun Tzu. One does not cease to be amazed at how this simple fact underlies the multi-million dollar intelligence gathering industry.
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.
Real-world events demonstrate our collective inability to rapidly and accurately observe, process, and interpret information in support of decision making. Additionally, one can argue that any sizable enterprise struggles to “know what it knows”. In other words, we often cannot answer questions completely or with certainty, despite the fact that we may hold the requisite data.
Topics: Semantic Web
The nature of the insurance industry is changing quickly, and much of that change is being attributed to big data and analytics. In fact, a Research and Markets report on the global insurtech market highlighted big data discovery and analytics as a key market trend that will drive a projected CAGR of 10.41 percent during the period 2016-2020.
We’d like to introduce you to the newest member of our team, Sam Chance, who has joined us as managing director of pre-sales. In this newly created position, Sam will work closely with the sales and engineering teams to accurately define and communicate the value of our Anzo Smart Data Lake® (ASDL) platform to our growing roster of customers, while also architecting a customized solution for their environments.
With compelling business use cases, adoption of open industry standards and enterprise deployment of high performing scalable platforms, 2016 was a breakout year for the adoption of semantic graph technology and the Smart Data Lake® in Financial Services.
Topics: Smart Data Lake
In this webinar Steve Hamby, Managing Director Government, discusses semantic graph technology to help Federal Government CIOs and their agency staff that are researching enterprise data management and mining tools understand how Smart Data Lakes can be a superior mechanism for addressing their top data priorities. Here are the slides from his presentation.