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Data without insights is useless and we all know how, getting meaningful insights in this Zettabyte era would be near impossible without Big Data technologies. In simple terms, Big Data is a collection and management of copious volumes of data, including structured and unstructured data. However, the ‘Big’ in Big Data is not so much about the volume, but rather its ability to gain actionable insights – either strategic or operational – from the data collected. Amazon and Netflix are classic examples for how big data is being used to automatically customize user experiences with data-fueled recommendations to optimize sales. These tech giants are masters at transforming insight into data-driven action.
While there are many Big Data success stories, there are those of failures too. But now, the technology is evolving and moving to a new stage of maturity with promises of even greater business impact and industry disruption. And as Big Data initiatives mature, businesses are now combining the agility of its processes with the scale of Artificial Intelligence (AI) to deliver greater business value.
So, what happens when the power of data driven insights meets the power of reasoning? What happens when Big Data meets AI?
The convergence of AI and Big Data will change the way future firms drive business value from their data and analytics capabilities. Though AI has been around for decades, it is only now that they can take advantage of datasets of sufficient size to provide meaningful insights. The availability of data in large volumes is enabling capabilities in AI and machine-learning that remained dormant for decades. It is this ability to readily access large volumes of data with agility that is leading to the rapid evolution in the application of AI and machine-learning applications.
Today cheaper parallel computation driven by Big Data, better machine learning algorithms such as recurrent neural networks and deep learning is empowering AI to provide real business breakthroughs that was never possible before. At a consumer level, Facebook is using deep learning, graph analysis and indexing to analyze, classify and serve up its users’ billions of photos via Photo Search, AI is transforming Google Search and Amazon’s AI engine helps it to predict product demand, power search rankings and detect fraud. AI is enabling back-office automation, such as recruitment, processing accounts payable and receivable, and message management – automation of responses to optimize knowledge transfer. Many of these applications are already at use in industries such as healthcare, finance, security, public services and supply chain management.
However, AI is not just about process automation, the real revolution that AI can bring about is in the area of business decision making – by truly accelerating the journey from insights to strategic decisions. Organizations are exploring ways to deploy Big Data and AI at a more strategic level. Large and complex organizations like Verizon, possessing massive amounts of data to be analyzed, are turning to Big Data and AI to help navigate the data complexity. The Big Data and Artificial Intelligence Systems group at Verizon employs large-scale machine learning both to improve Verizon’s infrastructure and to develop products in such areas as education, healthcare and the Internet of Things.
The impact of big data extends well beyond simple data and analytics. Big data and AI both together form the powerful foundation of heightened innovation and business disruption. While the first wave of big data was about speed and flexibility, it appears that the next wave of big data will be all about leveraging the power of AI and machine learning to deliver business value at scale.
Lymbyc, being the world's first virtual analyst has proven its mettle in the industry . Be it the "Most innovative Data science Product" by Aegis or "the top 10 emerging Analytics startups in India to watch out for in 2018" by Analytics India Magazine, Lymbyc is making heads turns and making headlines