One of the biggest issues facing companies is one that’s rarely discussed: redundancy. All too often, employees waste time searching for the same information over and over, which results in excessive onboarding and a lack of team cohesiveness. That’s where Big data comes in. Using big data, companies can connect individuals researching the same topics, enabling companies to foster collaboration and productivity at work. Today I’m speaking with the CEO of Collokia Pablo Brenner, whose company works in Big Data collaboration, to discuss the state of the industry and where big data should go from here.
1. Could you tell me a little about yourself and how you became interested in big data?
I'm a High Tech executive working in the field for over 3 decades. I graduated from the Technion (Israel Institute of technology) in 1987, at which point I started my career developing networking routers. In the early 90's, I cofounded Alvarion, which became one of the first companies in the high tech industry to develop WiFi products (as VP of R&D in Alvarion I was part of the Working Committee that defined the WiFi Protocol).
Following this venture, I moved back to Uruguay, and after pursuing several business endeavors, became the VP of Innovation at Globant, where my job was to engage with customers at early stages of product definitions.
In 2010, just before joining Globant, I attended the Singularity University Executive Program in Palo Alto, where i got a crash course on emerging technologies, including AI, Robotics, Nanotech and Biotech. At this point, I started researching a new technology called Hadoop and, months later, after reading an interesting paper from McKinsey about BigData, we decided to build the BigData practice at Globant. Following this development, I began visiting with customers to promote the benefits of BigData.
2. How can big data help companies with onboarding?
Big Data is helpful to understand context, and context is all you need to help people with onboarding.
The main problem with onboarding is that companies do the introduction during the first few weeks when the new employee has no idea about the details of their job. Everything is completely out of context. The best way to learn something is by doing it, so the key is to let people perform using collected team knowledge, and add training when needed.
3. How can big data help company morale?
Besides assisting with onboarding, big data can show who is interested in the same subjects so they can interact. Many people are too shy to ask for help, so they spend lots of time trying to solve problems that somebody else has already solved. By putting people in contact with each other, people become more collaborative/productive, and the whole company morale improves as a result.
Additionally, with Big Data we can learn what interests employees and use this information to assign them tasks that resonate with them, which is one of the big problems with young employees. I’ve found that Millennials are extremely productive when they do what fits their interests, but if they feel their job is not fulfilling, they will grow disenchanted and most likely move on.
4. How can companies maintain privacy when they employ big data?
Privacy is probably the main obstacle when deploying Big Data solutions in either the corporate or consumer space. People are becoming more aware of this issue, and in some instances they are right to be concerned. In my opinion the only way to deal with privacy is to consider it during the design phase of the product or service. For instance, in most cases you don’t need to keep information about the individual, so you can anonymize the data at the very beginning, without even writing in any disk. In our case, we design with the premise that sooner or later somebody may hack us, so the only way they will not be able to get private information is for us not to store it at all.
5. What are some challenges associated with big data?
I believe the main problem is the user perception of privacy, even more so than privacy itself. With so many people using our data, everybody has become a little paranoid about the situation, so we need to practice full transparency to gain the users trust.
The other issue is that Big Data became so popular that expectations were taken to the extreme. People thought that Big Data would solve all the world problems, and with every new technological advancement, we encountered a level of frustration. Fortunately, there is now more understanding on the real capabilities of Big Data so there is currently a much better match between the expectations and what Big Data can really deliver.
6. How do companies go about fixing these challenges?
I think everybody is becoming more aware of the challenges and working on solving them. In time, both companies and users will mature. For example, in the privacy space, companies will become more respectful of users privacy, and users will come to understand the pros and cons of the situation.
7. What big data stories have caught you eye in the news?
The Big Data story I found really intriguing was Google’s AI beating the Go world champion. Big data is one of the main drivers behind AI and deep learning, so I thought it was an incredible display of the technology at work. It also displays the great potential of Big Data and Data Science: creating machines that see what humans cannot.
8. How do you think the big data field will evolve over the next 5 years?
Big Data is one of the big enablers of Machine Learning (the other is increasing computing power of course), and Machine Learning, or Deep Learning, is revolutionizing Artificial Intelligence. 5 years ago we wouldn’t have dreamed of having autonomous cars. Now it’s possible that children in the near future won’t have to learn how to drive. We will see this explosion of AI innovation expanding into other areas as well, including healthcare, finance, legal, etc.
Obviously this raises some concerns including the status of current jobs and whether they will survive the coming years. For example, there are currently around 3 million truck drivers in the US who face being replaced by autonomous trucks, which will not only be cheaper but safer. The same will happen with many other professionals, including lawyers, analysts, teachers, etc. The jury is out on how to deal with this but one thing is for sure: it will happen sooner than most people expect.
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