“Volume, Variety, and Speed Are the Key Trends Driving Growth in Big Data Analytics” Says Poornima Ramaswamy

If gathering the right data is one thing, putting it all in perspective is quite another. In this context, data visualization software becomes not only an essential but critical tool in a data analyst's kitty. Visual elements convey complex data relationships and data-driven insights in a way that is easy to understand. At times, the very perception of simplicity in presenting data might mislead the data presenter into an altogether different realm deviating from the set goal, particularly when data keeps changing. Qlik Sense products play this game to the tee, leveraging real-time analytics and providing businesses with the vantage point they need. Analytics Insight has engaged in an exclusive interview with Poornima Ramaswamy, Chief Transformation Officer, Qlik.

1.Tell us how your company is contributing to the Big Data Analytics industry of the nation and how the company is benefiting the clients. 

The Indian big data analytics industry market has grown significantly in recent years, with numerous large and small businesses accelerating their digital transformation plan. India is also expected to become one of the largest big data analytics markets in the world with better use cases and significant opportunities for data scientists in the future.

We see this as a huge opportunity as businesses benefit from technologies like data integration and big data analytics by taking the guesswork out of the decision-making process. For example, Qlik Cloud provides a complete end-to-end solution comprising data integration (data streaming, data warehouse automation, transformation, etc.) and analytics (visualization, AutoML, alerts) under one roof. Combining these processes and technologies helps businesses analyse massive datasets, identify patterns and develop insights. And when these insights are specific enough to result in action, they are called 'actionable' insights.

In India, customers across various sectors including BFSI, retail, telecom, and the public sector have seen value in Qlik's data integration and analytics solution. HDFC, IndianOil, and Samvardhana Motherson Group are some such customers who have been able to:

• Conduct faster, more accurate analysis, planning, and business decisions.
• Reduce expenses by optimizing business processes and performance.
• Increase customer loyalty and lifetime value from a deeper understanding of customers and customer behaviour.
• Identify new markets and sources of revenue by analysing market trends and purchase behaviour.

One of the other prominent examples of Qlik's capabilities deployed for real-time data integration and to help improve decision-making is India's National Stock Exchange. NSE teams were able to provide data visibility to its numerous databases (trading data, clearing and settlement) and use data visualization to get alerts and generate insights. The results were discernible, too; the team was able to cut down on processing data on specific tasks from 3 hours to 30 minutes. In addition, they improved response times due to the real-time capabilities, which are essential for regulatory and compliance purposes.  

We are also targeting to raise data literacy across the board through initiatives such as the Data Literacy Project and Qlik Academic Program. We have a presence in over 800 colleges and universities across India for the Qlik Academic Program. Through such initiatives, we want to create an end-to-end ecosystem that enhances the data readiness of stakeholders within the corporate infrastructure and at the grassroots level.

2.Kindly share your point of view on the current scenario of Big Data Analytics and its future.
The way businesses generate, store, and access data is constantly changing. It also depends on each enterprise or business on whether to tap into an on-premise model, hybrid, or a native cloud service. They also deal with fragmented data silos created by the various business departments or through mergers and acquisitions. Distributed clouds are the norm because the data landscape is hybrid and will continue to be disparate because organizations pick solutions based on workload, cost, performance and governance requirements.  As a result, some notable trends will continue to evolve over the years: 

• The pandemic-induced working-from-home paradigm has mainly driven collaboration mining. Collaboration-mining at an early stage of the data pipeline allows teams to track, work together and obtain better insights at the end. 
• Data needs to be 'explainable' to understand the reason behind any actionable insight. Distributed data architecture poses a challenge, making it imperative for any organization to ensure that its data is identifiable with metadata, is of high quality, and that the teams can trust the sources. 
• AI will move deeper into the data pipeline. This does not indicate that AI used to automate the movement and transformation of data will do away with human intervention. It means that AI will accelerate the data pipeline management process and let expert data engineers and scientists focus on more complex problems.
• Citizen Data Scientists with non-technical backgrounds are taking advantage of application automation viz. AutoML to fill the gap between data and action. 
• The dashboard continues to evolve, moving from historical analysis to real-time visualization and AI-driven predictive analysis. 
• Security is a top priority when dealing with vast amounts of data. Analysing data from multiple repositories raises privacy, identity, and access management issues. Every region has regulatory norms, making trust-driven interoperability critical in the long run. 

3.What is your biggest USP that differentiates the company from competitors / What are the business benefits of handling data analytics & implementing a real-time decisioning platform?
Qlik helps organizations do more with their data and transform how they do business by moving from passive business intelligence to a state of 'active intelligence,' i.e., turning raw data into predictive and actionable insights. Customers do not have to migrate to a specific platform to use our SaaS solution. Qlik's data-agnostic solutions allow customers to tap into massive volumes of data to gain complete visibility.

Qlik Cloud also provides an end-to-end solution that combines data integration with data analytics so businesses can harness the correct data to deliver the best insights at the speed of business. 

Data-driven real-time decision-making helps a business adapt to changes faster. In logistics, for instance, deriving actionable insights at the speed of business makes the value chain much more resilient to disruptions. 

Qlik also believes in the democratization of data. By this, we mean that data access and analysis should also be in the hands of every employee. This improves response times, brings in fresh perspectives, and motivates employees to add value to the business. The Data Literacy Project by Qlik is an initiative that drives discussion about upskilling everybody with much-needed data literacy skills to improve their job prospects and employability.

4.What are the key trends driving the growth in Big Data analytics?
Data is generated all the time in several forms on various platforms. There is excellent intrinsic value in this data. Intrinsic because data integration and AI-driven big data analytics extract actionable insights from the raw data. All of this must occur in near real-time to achieve quicker response times. So, the key trends driving the growth in big data analytics would be volume, variety, speed at which insights are derived, and the value they provide.

5.How is Machine Learning (ML) shaping the Big Data industry today? How is it changing the role of CIOs and Leaders?
Low-code or no-code automation has helped streamline processes. Our low-code automation for Google BigQuery, for instance, offers nearly hands-free management and Qlik's no-code solution for optimised workflows helps cut down on time spent on programming repetitive tasks.

AutoML (Automated Machine Learning), for instance, helps business analysts and experts access and apply simple machine learning models to everyday operational business needs. Data scientists are very critical for any organization. By increasing the pool of data engineers who can create simple ML models, the more we can leverage these valued data science specialists for the most complex and strategic business problems and provide governance and support to the rest of the organization. At the CXO level, this kind of democratization takes some of the pressure off the leadership and brings in fresh perspectives from several quarters. 

6.Where do you see growth coming in for the sector?
The retail, financial, IT, and pharma sectors have been driving the growth of big data analytics. Besides these, there is also the manufacturing, agriculture, and government public sector that will drive further growth in the future. 

7.What is your Leadership Mantra?
Change is constant and an opportunity, much like data. It is intriguing to know about customers and their issues, and the way ideas and data can be applied to resolve their challenges, simultaneously learning in the process.

During the time of Covid 19, I've witnessed an unprecedented level of sharing, collaboration and openness among our customers, as we all responded to the COVID-19 pandemic. This growth and upswell of a compassionate, generous community, working together and through this global crisis, enabled us to help each other, driving business value transformation through data and insights – this became our mantra at Qlik.