How many times have organizations reached a “pivot point” concerning technologies? Trying to stay relevant is making businesses dizzy. Don’t get me wrong – pivots are often necessary for reaching the end goal, but spinning in circles doesn’t get an organization anywhere. 

From small mom-and-pop businesses to a multi-billion dollar franchises, big data and analytics appeal to everyone looking to improve their insights to better understand clientele and make more informed business decisions. Whether it’s the IT guy, the director of marketing, the company CPA or the vice president of operations – each role needs a lot:

Big data has become a hot topic. Yet, companies are all over the map in terms of understanding what big data is and how they can harness it to optimize their business processes and innovate within target markets. Big data adoption follows a classic maturity curve. After seeing specific and measurable benefits realized by early adopters, an increasing number of companies want to put big data to work, and those in the healthcare industry are no exception. The problem is they don’t know how.

There’s immense pressure in the marketplace for organizations to become data driven and utilize the flows of data in and out of the business. When an organization harnesses its data properly, many advantages can be gained. These benefits include an increase in competitive advantage, finding new revenue opportunities, increasing profitability, increasing customer service and satisfaction, as well as achieving operational efficiencies. Unfortunately for some, the promise of those benefits comes at a cost and real value is never realized.

The availability of information about products and services, from choosing a restaurant for lunch to implementing enterprise-wide analytics software, empowers modern consumers and businesses to become more educated and proactive than ever before. Such detailed data means the competition is more robust than in the past because these consumers can easily compare products and prices. Also, the expectations of the products and services’ derived value has increased. To be effective in getting through the noise to end customers, salespeople need to stand out as trusted advisors and leaders who add value and solve complex customer challenges.

Often in parallel with cognitive, you hear artificial intelligence (AI) referenced which seems to blur the lines of distinction between the two. In part one of the de-mystifying series, I discuss the driving factors for cognitive computing, let’s now break down this notion that AI and cognitive computing are one and the same.  In fact, there is an explicit difference between AI and cognitive computing.

With the technology landscape ever changing, it seems like there is a new hot buzzword online or acronym being thrown around phone calls every day. Oftentimes, words are used improperly or without a true understanding of their relationship to the technology at hand or business problem in question. It can be hard to sort through all of the noise.

IoT is one of the latest and most buzz-worthy acronyms to enter the technology scene in the last year. IoT, or the Internet of Things, is a term for the concept of embedding computing devices like sensors into everyday objects to allow those objects to send and receive data.