Interviews

Data analysis, A booming sector in India

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The scope and use of data analytics is not only a global phenomenon, but as it is turning out, India is being considered as a big market for data analytical skills sets, says Anthony Kilili, Head, Dunnhumby India & Global Head of Customer Engagement Science, in conversation with Elets News Network (ENN).

What are the new ways to analyse data? What about the future technologies to process data faster?

Anthony Kilili, Head, Dunnhumby India & Global Head of Customer Engagement Science,

Anthony Kilili, Head, Dunnhumby India & Global Head of Customer Engagement Science,

As a data science platform, dunnhumby is at the forefront of using retail data to understand the customer. We then apply this understanding towards implementing ‘Customer First’ solutions and provide unmatched shopping experiences through activations such as 1:1 personalised marketing activities both online and offline.

To achieve this, we process huge volumes of data at a rapid pace. With cheaper storage and faster computer processing, the amounts of data accumulated continue to grow through increased social connectedness and internet of things, among others. Given the vast variations in structure and velocity of the data, technologies have emerged to help scientists build the tools needed to navigate these waters. There is an increase in open-source systems which result in faster adoption of new methods and cloud-computing as well as distributed-computing which provide a lot more flexibility in how data is consumed.

In addition, we have seen drastic changes in consumer behaviors such as higher expectations regarding convenience and great shopping experiences. This means that businesses need to use sophisticated algorithms and methods to accurately determine and predict customer needs. We use artificial intelligence methods to drive these solutions. Through machine learning techniques, our algorithms can automatically and rapidly adapt to changes in behavior and data.

What is the difference between a data analyst and a data scientist? How their career distinguishes and upcoming trends in respective careers?

Data scientist is not a glorified term for data analyst. There are clear differences between the two.  A data scientist uses sophisticated analytical techniques to mine large amounts of structured and unstructured data to identify useful nuggets. To do this, they are skilled in data wrangling, programming, advanced statistics, complex algorithms and visualisation. They also have a strong academic curiosity and use these skills to predict future behaviors using data from disparate sources.

Data analysts will typically not require strong programming or predictive analytical skills. They work with structured data and packaged software to derive insights based on hypotheses. Typically, the data analyst does not build complex models using machine learning or advanced programming. They also create reports using various business intelligence tools such as MicroStrategy.

There is a projected global shortage of data scientists. India has, over the years prepared, well through a strong focus on science and technology. The country is well-poised to continue in its leadership position in the supply of talent around the world. Within India, there has been a rapid growth of startups seeking skilled data scientists hence the market provides a variety of choices for candidates from well-established organizations to startups and Data Science Research Hubs serving multiple clients.

Can a data analyst be turned into a data scientist? How?

Many business analysts can be trained into data scientists. A strong business analyst already has good domain knowledge and brings an understanding of the ‘why’ of the project. To grow into a data scientist, two other skillsets are essential. One is a strong programming acumen, which allows the scientist to manipulate structured and unstructured data using a variety of languages. The other is an understanding of advanced analytical algorithms appropriate for solving specific problems. Many analysts can quickly learn these and become data scientists but they need to have strong motivations due to the steep learning curve involved.

What are the career opportunities in retail analytics?

Until a few years back, the analytics market in India was primarily being driven by a handful of specialized analytics firms, that too predominantly in the BFSI space. But, the situation is very different now- we’ve seen a flurry of start-ups in this space, increasing amounts of companies setting up internal analytics wings across industries, separate from IT and Consulting firms, also getting into this space.

India is already among top 10 big data analytics markets in the world. Indian executives are upbeat about using analytics in leveraging it for decision making, not just for understanding what’s happened in the past but also forecasting for the future.

Organisations are increasingly realising that unless they infuse analytics within the functions in a significant way they cannot drive decisions and respond to the changing dynamics across industries. There are reports that over the next two years, a lot more organisations plan to invest $10 million or more for data and analytics resources.

 

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