Data is increasing in supply chain management for retailers. Most of this data is unstructured and flowing all day and night into servers, and there’s much more to come.
The Smart Grid is poised to transform the energy industry using digital information to enhance efficiencies and performance for utility customers. As the Smart Grid continues to expand, demand for advanced big data analytics capabilities to better manage grid operations is growing as well. Utilities are looking for ways to effectively manage the large volumes of complex and unstructured data flooding the network to provide real-time, predictive and highly actionable intelligence to the enterprise.
An organization’s staff is its most valuable asset, and the human resources function is critical to the stability and growth of business operations.
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.
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.
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.
"The legal and ethical collection and analysis of information regarding the capabilities, vulnerabilities, and intentions of business competitors" - Strategic and Competitive Intelligence Professionals
This is how Strategic and Competitive Intelligence Professionals (SCIP), the most well-known global body on Competitive Intelligence (CI), defines the concept of CI. For the uninitiated, the page on the organization's Code of Ethics for CI professionals sheds lights on the innards of the practice. One does not have to belabor the importance of the practice in the context of successfully operating a business. It is in the operational details, as is the case with most details, that the devil lies.
“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.”
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.