The panel discussion titled “Tech Solutions- Mobile and Big Data Analytics”, which was a part of Bengaluru Tech Summit 2017, a three-day tech festival that brought together global innovators and tech enthusiasts on one platform, saw experts from the big data and analytics industry talking about how these technologies have been offering solutions across various verticals.
Samir Kumar, Managing Director, Inventus, who was moderating the talk began the discussion by addressing that over the last 2-3 years, the startups that have been coming to him, have been pitching themselves as machine learning startups. “So much has been the popularity of these terms that every startup wants to be called a machine learning startup. To get my concepts clear on the subject, I took a course on Coursera, to identify if the startup really is what they are claiming to be.”
The adoption of analytics, artificial intelligence, machine learning has been so rampant that all the companies are adopting it to solve larger challenges. Ulla Koivukoski, Head of India Operation, Avanto Ventures explained a use case where they got analytics team deployed for their clients who applied predictive modelling to get their systems working fine. Everything went well and then they realised that the revenue went down. This is when they realised that though everything has been done perfectly and the data has been understood perfectly, but it came with limitations. “Even though data is unlimited but it comes with a lot of limitations, so we should be cognizant about it”, said Kumar.
Nipun Mehrotra, Chief Digital Officer, IBM added that though everybody is using machine learning and data but that doesn’t mean that it becomes a data company. The company might be sitting on a lot of data but may not be using it properly. To be able to use it in full efficiency can only make all the data worthwhile. “There is a new term in the market called Infonomics, which is nothing but economics of information and only when you think of data as revenue model is when it can reap benefits”, said Mehrotra.
Data has a lot of value and should be put to good use
Atul Jalan, CEO, Manthan said that data came as a byproduct of digitization and it is going to be the defining feature of one’s work. “It is not only the new oil but becomes a fodder for artificial intelligence and machine learning, which in many ways will extend our own abilities further”, he said.
Jalan also shared that he thinks artificial intelligence to be the new electricity and it is going to change our lives in so many ways—jobs, economy, being a few. “It is often feared that 65% of jobs would be gone but it is going to create millions of more opportunities. Such is the power of artificial intelligence that you can pick anything electric and make it cognitive”, he added.
Challenges in the space
In the current scenario, there are companies who have been buying systems and technologies but don’t know what the problem is and how it could be solved. Koivukoski said that organisation will have to restructure data to make sense of it. Vision has to be clear on what is to be done with the data. Looking at it fundamentally, it is important to make sense of it, shared Kumar.
Data privacy is another issue and there needs to be check on the unauthorized use of data. “There are some apps that only are available free of cost so that they can collect user data and monetize on it later on, which is unethical”, said Mehrotra. There needs to be strict regulatory body around it. He also clarified that data privacy and data security are two different things and should not be confused while considering challenges.
Linking data to external sources
The companies are collecting data and when we look at it, it can be used in traditional ways to use it and analyse it to get details like revenue impact, but using it for gaining external information like what customers have been buying other than our products, can have bigger impacts on businesses.
Mehrotra cited an example where they are helping companies build model to provide tyres as service and are trying to get driver analytics. Similarly, data from whether analytics has been used by insurance to find out crop pattern, land fertility, water bodies around, etc. and then decide on lending money to loan appliers. So there have been an overall linking of the data, which has been delivering larger benefits.
Structuring the data
The panelist resonated the thought that most of the data is unstructured and to reap the maximum benefits out of it, it is important to organize it first. “80% of data is unstructured”, said Jalan, and we need artificial intelligence even more because it can understand the unstructured data in the form of speech, emotion etc.
It can also open the doors to exploring new business opportunities. “Every problem is an opportunity for entrepreneurs”, said Kumar on a concluding note.
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