Analytics India Magazine had an exclusive chat with Yasmeen Ahmad, Customer Director (Central Europe, UK&I and Russia) for Teradata. In this conversation, Ahmad talks about analytics adoption by enterprises and what are the good strategies for analytics adoption. Ahmad comes from a data science background and currently works with large enterprises in the European Area. She also highlights her experience of working with enterprise leadership teams and how Teradata Vantage, the company’s newest offering which can help companies extract business value out of their data.
Analytics India Magazine: What is your role at Teradata and what is your background?
Yasmeen Ahmad: I am Director for Customer Excellence for Europe covering Germany, Switzerland and England. I come from a data science background and at Teradata, I work with our customers at a strategic level to help them understand how to use data and analytics to solve business problems. We also help them to overcome many industry problems where they have invested a lot in data analytics and have not derived any value. We try to unpack all these problems for our customers.
AIM: What are the best strategies or tactics for adopting AI and analytics for conventional enterprises who are new to it?
YA: In today’s world you have more access to data so you have to be strategic. Reports suggest that 90% of enterprises will have a Chief Data Officer very soon. This person’s role is to not only keep the data secure but also to make sure the organisation leverages the data and derives much value. They are concerned not only about how the data is stored or managed but also how it is used. With that kind of person in the organisation, there is a voice who is championing data and analytics at a strategic level. From there you have to invest in capabilities to bring in people and technology but I would suggest starting with business use cases first. A lot of our clients are big organisations who had invested in people and tools but still did not derive any value. So an enterprise needs to understand where is the biggest business challenge where data and analytics can make an impact. Having a business use case analytics road map is very important.
AIM: You underlined the importance of data champions in an enterprise. What is your experience of working with organisations who are not very convinced about data and analytics?
YA: There is a lot of noise in the market regarding AI and analytics. The top management always hears about terms like AI and cloud. These are big trends which are on their radar. They are already aware that AI is going to have a big impact on their businesses and they need to be thinking about cloud. But they don’t have all the technical know-how necessary to understand which tools and technologies will help them achieve business outcomes. We have some banks in the UK who are ready to invest hundreds of millions in digital transformation. From a Teradata perspective ask businesses to not lock themselves in because the technology landscape is moving quickly. Cloud will continue improving and you would require a hybrid solution and similarly we launched Teradata Vantage to give customers the power of plug and play. The engine can be used as a plug and play solution and can be accessed via APIs with integration points because technologies keep on changing and we want to provide access tools that deliver value.
AIM: Coming to Teradata Vantage, what specific features in Vantage are customers responding to?
YA: Firstly, Vantage is for 100% of the data. So customers are really responding to the fact that we have built a data layer where 100% of their data is going to land. Many data streams come together to derive value. Vantage can connect to S3 and Hadoop to have a good view of the data. Another thing that the customers are responding to the availability of multiple engines. Because today businesses now understand if they have access to multiple analytical techniques they can get much more powerful techniques. If you are detecting fraud, you will not have great results using only decision trees, you use neural networks and then combine. So our customers like this plug and play mode and have access to flexibility. You don’t have to move much data around, you can operate on the same data with different algorithms on one engine.
AIM: Why were the large enterprises disappointed with analytics solutions available? What were the top two concerns?
YA: I always ask my customers this question. Do you want to be an early adopter or a fast follower? Actually, for a top 500 firm, we work with they want to a fast follower. Many companies with the onslaught of data analytics solutions, went out and used many solutions which was out there. The reality is that more than half of those tools and technologies will never get production ready because someone has created in a garage and it never reaches a level of maturity which can be used by enterprises and gains traction on the market. Our customers have decided that they want to play with new technologies like deep learning but only if they bring value. They want to have some confidence in the technology.
AIM: You work heavily in Europe, what is the difference between the Indian and European markets?
YA: I don’t have a straightforward answer to that question. We are part of the “Future of Marketing Network” run by Oxford University in the UK. From the hyper personalisation point of view one of the big trends in the UK are voice activated commands with the advent of Amazon Alexa and Google Home. We are working with a retailer to how to market a product to a machine rather than a person. Because you tell Alexa, “Put toothpaste in the basket”, you don’t mention a particular toothpaste brand and merchant. In markets like the UK these devices are really blowing up but with India, it will really take some time for these technologies and devices to catch up. That is an example of the difference between the two markets.
Try deep learning using MATLAB