AI in Big Data and Business Analytics is Striding Ahead

While AI and machine learning have been around for a while now, their recent advancements have been increasing at unprecedented rates and with this level of growth, comes the potential to implement the technologies into various fields to help to combat the world’s most pressing issues.

AI is not only helping commercial business verticals with data problems but is also assisting non-profit organizations in ground-breaking innovations towards sustainability problems, from solving complex problems through iteration to saving resources through automation to gathering and visualizing data, AI has incredible potential for good.

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According to IDC, worldwide revenues for big data and business analytics will grow from USD 130.1 billion in 2016 to more than USD 203 billion in 2020, at a Compound Annual Growth Rate (CAGR) of 11.7%. By 2020, more than 50% of data and analytics service engagements will be AI-enabled, up from 10% in 2017.

Gramener is a design-led data science company with the aim to generate insights data and inform key decisions through interactive visualizations. The company recently won the CNBC – Microsoft award for ‘Empowering Societal Progress with AI’. It has created a deep learning AI application to track the decrease of endangered species over time, which provides data to researchers and helps them prevent further population decline.

Gramener is building data applications and leveraging them to bring out insights as data stories. With the help of interactive visualizations and simple human-like narratives, they make business data consumption easy. They aid in scalability without the cost and automate human intelligence using AI techniques.

The company provides a data science platform that will increase enterprise analytics applications build by 50%. They claim that their platform is modular and component driven with no vendor lock-in and extensible with future technology scalability.

The combination of AI with autonomous things solves enterprise problems by augmenting customer journey analytics through AI and interactive data visualizations, which in turn provide great experience for users.

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Anand S, the CEO and co-founder of Gramener, is an IIT Madras alumnus. Taking off from there, Anand was drawn into the maze of data and his initial tools were Linux based grep, sed and awk. He then moved on to Shell scripts and PERL and today architected the Data Science platform Gramex. “Tools are never the concern, the motive and the execution is,” believes Anand.

Enterprise decision makers often suffer from issues such as too many reports, because easy-to-use business intelligence tools create a surplus of reports that are not always useful. Also, analysts often lack the knowledge of what is useful for the business and business users cannot interpret the data. Moreover, insight generation and consumption is mostly manual and data is not available for decisions in time. While enterprises have access to information, but the gap between data science and business impact is too wide; Gramener is trying to help bridge this gap.

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