One can aptly describe many of today’s organizations as complex adaptive systems. Dynamic interaction patterns and emergent relationships characterize their complexity, while their ability to change and self-organize capture their adaptiveness. To survive, traditional mechanistic, highly structured organizations characterized by rigid, vertical communications have transformed to organic, rapidly changing organizations that exhibit nearly amorphous communication patterns. Organizations that learn to adapt usually survive or even thrive; conversely, those that don’t adapt, either dissolve or become insignificant.
Superior decision making is an essential aspect of life, whether it be in business, national security, health, environment, and every other aspect of human existence. Look no further than geopolitical affairs, such as North Korean or Iranian relations, to understand the importance and impact of decisions on human life, indeed the entire planet. This is not an exaggeration. From an Information Technology point of view, the goal is to provide complete and accurate information on demand to support decision making.
At the Gartner Data & Analytics Summit 2017, Cambridge Semantics' very own Barry Zane, Vice President of Engineering, and Ben Szekely, Vice President of Solutions, discussed how the Anzo Smart Data Lake® (ASDL) solution empowers business users with on-demand analytics of their rich data during their session entitled “Accelerating Insight with High Octane, Graph Fueled Data.”
At Gartner's Data & Analytics Summit 2017, Alok Prasad, President of Cambridge Semantics, was joined by Peter Horowitz of PricewaterhouseCoopers for their session entitled “Accelerating Insight: Smart Data Lake Customer Success Stories”. During this presentation, they discussed how Cambridge Semantics’ in-memory, massively parallel, semantic graph-based platform, Anzo Smart Data Lake®, delivers an accelerating edge to data-driven organizations, while maintaining trust with data security and governance.
Real-world events demonstrate our inability to understand rapidly and accurately what we already know. In other words, we cannot answer questions completely, despite the fact that we may hold the requisite data. For example, if someone attempted to enter the United States (US) at an airport, and US officials initiated a query to the “system” and found nothing, that person may enter the US erroneously. This might occur because US officials asking a question such as “What do we know about this person?” cannot assuredly answer it – and not in a timely fashion.
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.
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.”
As we approach the end of 2016, we sat down with our CEO, Chuck Pieper, to discuss the future of big data and get his predictions for 2017. Here are his thoughts.
In September 2016 Cambridge Semantics attended Strata+Hadoop World 2016 in New York, NY. While we were there, Marty Loughlin, our VP of Financial Services, spoke to a gathering of attendees about who we are and what our platform does. Here is his presentation.
A picture is worth a thousand words they say, and this remains true for data discovery and analytics. For centuries, graphs and maps have been used to help us simplify, understand and convey large amounts of data in a universal manner. And with the evolution of technology, we can now visualize increasingly complex information at lightning-fast speeds.