AI and data science are the buzzwords of today’s tech world. The related courses are gaining popularity and more and more young people are getting inclined towards them. The idea is to make data analytics more familiar to people to encourage involvement at all levels. People have mostly been associating data to mathematics and this acts as a restraining factor for people from non-science or non-mathematics background to take up data and AI-related jobs or courses.

In our latest INDIAai Conversations Jibu Elias talked to Srikripa Srinivasan, Vice President, Dell Global Analytics to demystify data science and analytics. Srikripa believes that variety is the spice of life and that is quite evident in her career and journey so far. She has a wonderful career of over 25 years as a finance professional and in global analytics in fortune 100 companies.

She has been responsible for roles ranging from core audit in Big 4s to FMCG sales and marketing, manufacturing, core sales in Finance and IT.

Her personal goal has been to support businesses to innovate to cope with the changing times with an integral philosophy of “customer first”. Change and transformation are constant; you can choose to stay put, change or transform.

The transition from an Economics scholar to a Chartered Accountant by profession, and now a VP Data analytics 

Srikripa believes that in 1994 while she was working as a CA, she was dealing with massive data and that was her first experience with it. The motivation behind choosing data and chartered accountancy was getting intelligence out of data, which was a challenge even back then. 

“The sole reason for taking up this job is the love for data.” Said Srikripa. She added that with her passion for data, she could add value to what she is doing currently. There is a belief among people that maths and data or analytics are closely associated however it actually isn’t the case. Srikripa explained that the backbone of analytics is not maths, it is the comfort with data that makes a difference.

India is said to be data-rich however, it is also said to be technologically poor. Comments?

India definitely is data-rich. We have data in all forms from regionally diverse data to various types such as audio/video, data in various languages, cultures, and so many more ways. To make the most out of this data there are 4 things to be ready with as explained by Srikripa:

1. Data source is of utmost importance 
2. Technology that can combine and churn results out of all that data 
3. Bringing the resulting data together and deducing a trending analysis or intelligence out of it
4. Syncing up the deduced intelligence with the customer needs 

“Data is growing exponentially in the world in various forms. India undoubtedly is data-rich however it would be wrong to say that we are technologically poor. We have a “problem of plenty” when it comes to technology in India. Too many opportunities are there as far as technology is concerned which creates confusion. We need to understand which technology we must pursue or direct our efforts to be successful in the long run. We shall acquire the agility and the ability to customize technology,” asserts Srikripa.

“We need annual technology check-ups to understand what is most critical and what would reap the best results just like our own health checkups.”

She added that scalability and flexibility are two important features to understand the long term benefits of any particular technology.

Work done by Dell’s Global Analytics Group

Dell Global Analytics Group rolls up under the large organization, Performance Analytics Group. There is a workaround master data analytics of recording multiple data points of end to end customer interactions. Product quality, inventory requirement, quality of the inventory, the efficiency of servers, financial services, payment tracking, customer satisfaction, and analytics around the workforce are all the fields where the team is working in finding ways to convert data into actionable results.  

Has the fear around data, analytics, and maths led to some gender disparity in terms of involvement in data analytics?

Yes, absolutely! Talking about data, the reality is that there are plenty of tools and techniques that we have today, using which we can really churn out the desired results if we have a basic knowledge of the fundamentals behind. At the first level, you need to have comfort with data and should not get overwhelmed with huge data sets. That's exactly the idea behind early education around data analytics which in turn would encourage more women participation in data analytics. The fear of mathematics or STEM subjects needs to be dealt with early in order to have progressed in the area.

On equality and diversity, and the major challenges that organizations face

Srikripa is a champion of equality and diversity and hence has been closely working around maintaining a healthy gender diversity as well as diversity and equality throughout the organization. She stated that we do have disparity as we go up in the organisational value chain in terms of seniority. We need to increase the volumes along with focusing on the quality of the talent with diverse backgrounds.

When asked about what could resolve and improve the diversity and equality at the workplace for data, analytics, and AI jobs Srikripa shared. “One reason could be extended work hours or flexibility issues that organisations once had. However, during the pandemic, the scenarios changed and organisations are keeping in mind that they should provide a comfortable work environment based on the employee's requirements. Creating a conducive environment for people with diverse backwoods or age, location or country of origin might bring a wonderful change in the amount of people who sign up for these job roles.”

“Another reason I will quote here is that data analytics is all about amalgamating the theory with the outcomes. We need people to connect the dots and present it to the world in a way that they can relate to. Visualization and storytelling are very important. Women are known to be good at visualisation but they seldom say it aloud to the world. This is where proper role modelling can help. Seeing other women or any role model can boost more people up to weave and present their stories through their work in data and AI” she added. 

“The third aspect is to get rid of apprehensions and have faith and confidence that will motivate you to sail through with whatever comes.” 

Views on hysteria around job losses due to AI

“Acquiring skills is the best way out there. Till the time you are keen on updating urself with the right skill sets you can never be redundant.” 

Human expertise is necessary for providing a seamless AI experience be it in any field. Continuous learning is the key that will help you evolve and stay relevant.

Take on responsible AI and privacy

Very very important! Ethical AI is highly critical in terms of how we are using it. Data sources are very important and hence keep checking if the data source right and not violating any privacy or ownership rights. With the amount of free data available today it becomes even more important to consider the data source. 

For the public as a message Srikripa said “Be clear and aware about where you want your personal data to be tracked for and also understand what you are not okay being tracked for.”

Message for the students with non STEM streams or humanities backgrounds who aspire to streamline their career

She concluded with a message “Get your hands dirty, try new things and if that is the attitude you carry the world of opportunities awaits. Don’t make decisions early in life, this might confine or limit your opportunities. Be more flexible recognize the chances and jump deep into it.”