Latest Tech Trends in Business Analytics
Varun Babbar is Managing Director for Qlik India &SAARC. Coming from a strong technical background, he started his career at Qlik in 2011, where he held the position of Director of Presales for India. Before joining Qlik, he spent more than a decade in various leadership roles managing clients in Switzerland, USA & India at both IBM and Infosys. Varun graduated with a Bachelor of Engineering from Thapar Institute of Engineering and Technology, Patiala before completing a postgraduate degree in Business Management & Strategy from IIM, Indore.
In a recent interaction with Siliconindia, Varun Babbar, Managing Director - India & SAARC, Qlik shared his thoughts on the current business analytics scenario and various other related aspects. Below are a few key portions of the exclusive interview
How do you see the business analytics market in India today?
We are living in the data moment; and Indian companies are strategically poised to extract more value from their data and improve their bottom line. According to IDC, Big Data and Analytics spending in Asia-Pacific will reach $42.2 billion in 2023 and $70.7 billion by 2026. Also, investments in enterprise investment solutions will remain the same owing to the incremental demand of organizations to engage in data-driven decision-making. Furthermore, the business analytics market in India is expected to grow at a CAGR of 21.6 percent between 2022 and 2027. Complexity around data volumes, data sources & disparate data and the increase in data generation at individual & organisational levels are some of the key factors driving this market growth today. Early adopters of analytics such as BFSI and Retail & e-Commerce have made significant progress in their analytics maturity, and BFSI is emerging as a top contributor to the market.
How are modern day technologies disrupting the business analytics space? Explain with a few cases.
AI is now at the forefront of analytics wherein companies are using it to make their business as efficient as possible. The next wave of AI is enabled by emerging topics such as transformer models, decision intelligence, graph technology, simulations, composite AI, synthetic data, and AI engineering. However, what’s common amongst them is bringing AI to the next level by creating more business impact and overcoming the limitations of current AI. As a consequence, AI continues to improve in adaptability and versatility.
On the other hand, although data management remains a challenge in complex modern environments, data fabrics offer solutions to manage and enhance data pipelines, especially when focusing on targeted and practical use cases tied to business requirements. Practical data fabrics leverage individual data domains or specific types of metadata to enable business use cases like data sharing while creating a foundation for comprehensive, automated, future data pipeline designs. Data and analytics ecosystem capabilities like data lineage, data observability and data catalogs are enabled by metadata-driven data fabrics.
Tell us about a few important factors every organization must keep in mind when selecting a business analytics solution?
While visual self-service for end users augmented by AI for automated insights remains a significant use case, there’s a growing focus on the needs of the analytic content consumer. Platforms with capabilities for users to easily compose low-code/no-code automation workflows and applications can help to expand the vision for analytics beyond simply delivering datasets and presenting dashboards. In addition to the increasing consumer design focus trend, there’s the need for improved analytic content creation and dissemination governance.
Some of these critical capabilities that are driving the demand for analytics and business intelligence platforms are Automated Insights, which provides companies the ability to apply ML techniques to automatically generate insights for end users. Second is Data Storytelling, which is the ability to combine interactive data visualization with narrative techniques to package and deliver insights in a compelling, easily understood form for presentation to decision makers Third is the Data Visualization which offers support for highly interactive dashboards and exploration of data through the manipulation of chart images. Also, Governance capabilities track usage and manage how information is shared and promoted, while natural language query (NLQ) capability enables users to ask questions of the data using terms that are either typed into a search box or spoken
In what ways do you expect the industry to evolve going forward?
In the coming years, the reliance on emerging data streams and AI’s power to address growth challenges is paramount as businesses face achieving more with their data while confronting ongoing changes and resource constraints. Also, we hope to see data becoming ingrained in every decision, interaction, and process. Employees will naturally use data to support their work, allowing faster problem-solving and better decision-making. Automation of routine tasks will free- up employees time to focus on innovation, collaboration, and communication. This data-driven culture will drive continuous improvement and create exceptional customer and employee experiences while enabling the development of advanced new applications.
With vast networks of connected devices transmitting data and insights, new technologies like kappa or lambda architectures are expected to enable faster and more powerful insights. As cloud computing costs decrease and ‘in-memory’ data tools become more powerful, even sophisticated advanced analytics will soon become accessible to all organizations, in turn opening-up numerous advanced use cases for delivering insights to customers, employees, and partners. Also, it is more likely that CDOs and their teams will soon begin functioning as a business unit with P&L responsibilities and partner with business teams to ideate new data uses, develop a holistic data strategy, and incubate revenue-generating data services.
