As water is to fish, Data Analytics and AI are to Digital Transformation: Nirlap Vora, SAS India

To meet changing business and market requirements, digital transformation is the process of employing digital technology to build business.

Aanchal Ghatak
New Update
Digital Transformation

Digital technology have been enthusiastically adopted by Indian customers. Success with digital programmes has always necessitated accurate, full, and timely data.


Data and analytics are both critical components of a company's successful digital transformation. To get the most out of their business transactions and operations, companies must embrace digital transformation. A company's ability to meet the wants and desires of its customers will be limited if it does not undergo digital transformation.

In an interview Nirlap Vora, Director, Customer Success, SAS India, tells more. Excerpts:

Nirlap Vora

DQ: Why are Data Analytics and AI key for digital transformation and role they play in successful digital transformation?

Nirlap:  As water is to fish, Data Analytics and AI are to Digital Transformation.

A study from Infosys says 98% of organizations that use AI for their Digital Transformation generate an additional 15% in revenue.


As business’ continue to embark on their Digital Transformation journey, humongous amount of data is created; in fact data is said to be the new oil. But, just as a refinery is needed to make oil usable, creating the right insights by applying analytics on the data (and the use of AI to harness these insights automatically and faster) makes the data usable, thereby, making Data Analytics and AI the most critical aspect of Digital Transformation.

Organizations need to meet rapidly changing business demands from stakeholders who are increasingly relying on data and analytics to make a variety of decisions.  

The value of data analytics in digital transformation comes from the ability of an organization to combine both of them in their efforts to enable both the digitization and automation of business operations. This digitization and automation is what improves efficiency, spurs innovation and leads to new business models. 


AI further fastens and improves the process to not only generate insights to make the right decisions and drive success but also to action upon the data. AI can help organizations across all their key functions: right from catering to customers and providing contextual experiences to automating insights to automating processes to even helping organizations take key decisions in a matter of milli-seconds versus weeks or months by manual processes. 

Using AI and ML in planning and implementing a digital transformation puts businesses and organizations in a position to stay ahead of the curve. With AI and ML, information is analyzed in real-time to increase responsiveness to changes in customer behaviour and events and make business processes including IT operations more efficient. 

DQ: When creating new revenue streams through digital transformation what is the role of data analytics and AI?


NirlapData Analytics and AI can help organizations with forecasting, real-time visualization, faster insights and also in making the right decisions while creating new revenue streams. Analytics and AI in fact form the base of new revenue streams as they can help organizations predict and decide what streams to focus on and plan their strategy around it. 

If you look at it, any process starts with comprehending the situation and using that understanding to make a decision. For instance, I read this question, understood it and then I decide to formulate my answer. Similarly, while an organization is creating a new revenue stream, it is critical to harness insights from the already available data and run predictive AI models to not only understand what streams to focus on but to also automate the processes right from customer experience to company resource applications and even operations. 

By embedding Data Analytics and AI, organizations can see results faster and drive revenue more optimally than organizations who do not focus on Data Analytics and AI. Data Analytics and AI can also help in providing quick insights into company processes which can help enhance and reshape customer experience, market product more effectively and in turn see the impact of revenue and all of this in real-time. Data Analytics and AI also directly impact revenue and decrease costs, a Mckinsey survey in large enterprises found that over 27% of enterprises report at least 5% of EBIT attributable directly to AI and most enterprises also see >20% cost reductions via the use of Data Analytics and AI.


DQ: What’s the key difference between sectors in maturity and the readiness to implement Digital Transformation projects specially in India?

Nirlap: Digital Transformation has seen an unprecedented growth across the globe and in India in the last few years, a lot of which is catalysed by the Covid pandemic. Digital adoption moved 5+ years forward in a matter of few months and in the last two years digital adoption has further increased. India is in the forefront of this transformation, in fact a recent Mckinsey study on digital transformation lists India as the 2nd fastest digitizing economy in the world. 

Digital Transformation in India has seen a big uptick both in the public sector and the private sector. In the public sector, transformations such as Aadhar and GST have brought 1.2 billion people and 10 million business online respectively. The Digital India initiative by the government is also propelling Digital Transformation in the country. Energy & Utilities, Oil & Gas, Tourism are also undergoing transformation (albeit the scale today is not as large) as they understand how digitization, data analytics, AI/ML and contextual experiences can help grow their business’ faster and also optimize costs. It is also very exciting and interesting to see the government adopt cloud first technologies and we see a propel towards faster digital transformation in the next few years. 


The private sector, on the other hand is also seeing a massive transformation and by scale, is of course, much greater than the public sector. In the private sector, the BFSI vertical is the largest and the fastest growing category. In the last 2 years, we have seen almost every single BFSI organization transform the way they do business: right from bettering and providing contextual experiences to customers to using analytics/AI to harness right insights and make the right decisions. Telecom is another vertical which has invested massively in Digital Transformation, the fact that the 3 major Telcos of the country are now more Digital Service Providers offering services such as Data Centres, Media & Entertainment, Digital Payments, etc indicates the importance and the investment being made in Digital Transformation by Telecom Players. Retail, Healthcare and Manufacturing were a little late to start the race but have now embarked on their Digital Transformation journey and are not too far behind. 

Whether public sector or private sector, Data Analytics and AI are playing a vital role in the transformation and will be the key pillars to support the transformation in the next few years. 

DQ: What is the speed of cloud adoption – both globally as well as in India

Nirlap: Cloud is becoming a norm when it comes to data and analytics workloads. Organizations are looking to move their workloads from on-premises to cloud in a phased, smart and cost-effective manner. Just taking existing analytics toolset and moving them to the cloud—i.e., “lift-and-shift”—will not automatically yield the benefits that cloud-native infrastructure, systems and services can provide. 

Processing, storing and analyzing analytical workloads on existing on-premises storage and infrastructure is becoming expensive. As more users become interested in wide use and adoption of analytics, taking advantage of elastic cloud-native infrastructure and services might be beneficial. Additionally leveraging latest data compression techniques, co-location of analytics closer to distributed database, and reducing data movement will help. 

  • According to IDC forecasts, worldwide "Whole Cloud" Spending is expected to reach $1.3 Trillion by 2025. As businesses pivot to a digital-first economy, cloud will continue to play an ever greater, and even dominant, role as the IT industry focuses on delivering greater efficiency, flexibility, and faster innovation. We have seen a much higher adoption of cloud in developed markets like the US and Europe where there are clear regulations and standards already in place for a cloud first strategy. Majority of our customers adopting cloud are from these markets. Saying so we do see a lot more adoption of customers moving to the cloud over the last 2-3 years in India as well. The pandemic although unwarranted drove more awareness on digital transformation and cloud adoption. We saw a lot more Banks, Insurance organizations and even Retailers to that extent acknowledge the scalability, agility and ease of moving workloads to the cloud. Although, quite a few organizations are using Cloud platforms to speed up the process, what is important is to apply the right software technology to take full advantage of your current infrastructure. 

DQ: While embarking on digital transformation projects why do enterprises need to think about data security on the cloud

Nirlap: Data security, commonly referred to as the confidentiality, availability and integrity of data is essentially all the practices and processes that are in place to ensure data isn’t being used or accessed by unauthorized individuals or parties. 

When implementing hosted offerings, enterprises need to work with cloud providers to determine the most appropriate data classification level for information hosted in each solution. It is important to understand and classify data under own or cloud providers custody into either: public, internal use only, confidential or restricted. There is of course no room for complacency while managing data on the cloud and hence standardized procedures are required for handling data at each level of classification. At the same time, enterprises need to ensure and use the right level encryption/hashing and tokenization to protect their data both at rest and while in transit. 

We realize that there is no silver-bullet answer to security. It is about covering all the bases, continuously improving and benchmarking against current best practices. Security encompasses people, process and technology, and it requires the investment and focus of senior management.

data-analytics digital-india digital-transformation