Is Big Data The Land Of Analysts Or Scientists?
Who your brands needs boils down to the kind of data these professionals work on.
The ancient Indian festival Diwali, the “festival of lights,” takes place at the end of this month, and brands are bracing for a surge in online sales.
India’s big three e-retailers–Flipkart, Amazon, and Snapdeal–have been hosting festival sales for a number of years and have done so extremely effectively. Using big data analytics, these e-commerce giants have been predicting trends such as “festival sales” and learning more about the consumer, preparing themselves logistically for projected demand in products.
As such, the roles of data scientists and analysts are now vital, despite being increasingly blurred.
No Clear Demarcation
Companies are employing these data analysts and scientists to uncover the insights hidden in the depths of consumer data. But there is no clear demarcation of these roles, which often causes overlap given both are responsible for data management and insights. The difference, however, lies in the kind of data these professionals work on.
Indian e-retailer Tata CLiQ prides itself in delivering highly customised and personalised experiences, even during busy sales times.
“Like in any relationship, it’s really important to understand the person behind the purchase,” said Prathyusha Agarwal, Tata CLiQ’s head of marketing. “We’ve created a data warehouse that integrates the data from multiple touch points, such as supply chain, commerce, and partner interfaces across customers, products, sellers, and transactions. This helps us understand the customer’s journey and to better respond to their individual needs in real time.”
The key role of data scientists at Tata CLiQ is to convert raw data into comprehensive information through advanced statistics, analytical approaches, and machine learning. They work on all kinds of data–structured, unstructured, numeric, and nonnumeric–interpreting the information for valuable and actionable insights for the future.
Data analysts, on the other hand, work predominantly with structured or semi-structured numeric data provide business intelligence reports, summarise business insights, and visually represent this information on performance dashboards. Their key role is to collect, sort, and study different kinds of data sets across functional and consumer touch points and offer input into business decision making.
“Data analysts often perform basic analysis by slicing and dicing the data based on different business criteria,” explained Durjoy Patranabish, senior vice president, analytics, at Blueocean Market Intelligence. “On the other hand, data scientists apply mathematical or statistical skills in the areas of machine learning or artificial intelligence to derive deeper and predictive insights from the data.”
Why Have Data Specialists In The First Place?
Big data analytics has become the lifeblood of brands with a growing need for consumer insights and purchasing patterns. The analytics industry in India is expected to grow to $16 billion by 2025, from $2 billion this year, according to the National Association of Software and Services Companies (Nasscom).
The major industries responsible for this increase in demand include banking, financial services, and insurance (BFSI), retail, health care, and telecommunications. Nasscom predicts that India will become the data analytics and big data hub of the world. This predicted increase emphasises the greater need for data specialists who can provide valuable and rare insights for marketers and their brands.
Companies that treat analytics as a strategy rather than merely a function will be able to better harness its power, said Ajay Kelkar, chief operating officer and co-founder of marketing analytics firm Hansa Cequity. But companies face several hurdles in adopting analytics.
“One of the great difficulties is that it can be difficult to explain and understand; it is widely held that analytics specialists don’t communicate well with decision makers and vice-versa,” he said. “As a result, adopting analytics is still not easy within companies. Brands only benefit from analytics when they treat it as a deeper company strategy.”
While leading companies like Flipkart, Amazon, and Snapdeal use analytics to support busy periods, such as their festival sales, success for other brands will depend on how well they integrate data experts into their businesses and how they communicate their insights to decision makers.