So far in this blog series, I have identified the driving factors for cognitive computing and the differences between artificial intelligence and cognitive. Having a better grasp of cognitive computing context is valuable, but let’s focus on how you can apply it to your end-customers for solving their data-driven issues. Who or what would benefit from cognitive technologies?

May was a busy month for Data Analytics and IoT with conferences including IoT World, IBM Vision, Informatica World and SAP Sapphire.  As industry leaders descended upon California and Florida, Tech Data was onsite to press the flesh, talk to customers, and gain a deeper understanding of business needs and use cases.

Data is, and will continue to be, at the core of our digital world.  Considering data as a currency not only validates the importance of data, but strategically shows a smarter use for it.  Actionable insights from unified data are key for advancing digital experiences and improving business decisions.

I have spent many years working with business partners, and as I consider the many partners I have worked with, there is a type of business that always seems to do very well. It’s the companies that identify themselves according to their specific capability strength (e.g. analytics, collaboration, security), as opposed to vendor expertise (e.g. IBM, Oracle, HP).  Instead of saying “we are true blue,” meaning that all they do is IBM, they say, “we are an IT consulting firm specializing in analytics”, or “we are Enterprise Security experts”.

I recently had the opportunity to participate in a series of panel discussions as part of a Big Data and Hadoop roadshow conducted by Avnet, HPE, Hortonworks and Suse.

Currently there are 1.6+ million Android Apps and 1.5+ million iPhone apps. Allow that to “sync” in for a second. There are 3.1+ million mobile apps floating around in cyber space. If that were people, that would be larger than the population of Toronto and almost the size of Chicago! It is both absurd and awesome at the same time. However, the insanity goes beyond just the number of apps. After all, the apps on our phones are just the tip of the iceberg. There are many things we have not considered behind that flashy user interface. For example, if there are 2.5+ million mobile apps, how many integration services, databases, security profiles, etc. are there? That’s where it gets a little more crazy exciting.

As the hype around big data is starting to fade, the hard work of implementation begins for many organizations. I’d like to share some of the most valuable lessons we, at Avnet, have learned so far on our journey to big data success.

You’ve heard it before – data is the lifeblood of every organization. Every business has it, and when data mining and analytics are applied to expose the valuable business information embedded in data, an organization of any size can improve performance and decision quality, while uncovering the knowledge in order to advance and compete. Growing at an unstoppable rate, the possibilities ahead with big data and analytics are endless.

Anyone that knows me knows that I am the furthest thing from a sports fan. Although, while I have no basic understanding of sports, I do know technology and the many ways that data is changing the industry and becoming even more powerful in our daily lives. The use of analytics as a daily practice is growing at an unstoppable rate, so it’s no surprise that the sporting industry has also learned to take advantage of it as well. In the article below written for StraitsTimes, author Rick Scurfield, general manager, NetApp (APAC) discusses how unstructured data from live sporting events, such as tennis tournaments to F1 racing is analyzed and being used effectively to improve individual and team performance. Although most of the data mining is done behind the scenes at live sporting events, I see this in action everyday working for and with technology companies- Helping them find meaning in their data as well as storing, protecting and retrieving it when their team is counting on it.

In the past, the term “big data” has served as a catch all phrase for the massive amounts of information available and collected in the digital world. Today, big data is being called the emerging power of the 21st century and is serving as much more than a buzzword, acting as a huge disruptor in the technology channel. With a growth rate of 50% a year, harnessing all of the components of big data presents a real challenge.