We are looking at the onset of an algorithm economy: Yen Yen Tan, Managing Director, SAS South Asia Pacific

Big data  is coming into prominence among organizations, in showing them untapped opportunities and markets. Yen Yen Tan, Regional Vice-President and Managing Director, SAS South Asia Pacific discusses SAS’s new investments and analytics trend which will shape the market.

SAS has forayed into with SAS Cybersecurity. How is its uptake in Indian sub-continent?

The focus on cybersecurity comes from our background in analytics in real-time. Our focus will be more around Fraud & Risk area. It is relatively new as our first go-to markets are US and Europe. Recently, we have also been receiving interest from India. The solution is at the foundation of analytics solution in the organization. Presently, our customers are looking at more 360 degree view of their customers to give them more personalized experience. The marketing also want to give more real-time campaigns and personalized campaigns to customers. They also want to acquire more customers based on segmentation. This gives us a very positive view ahead of the solution. We are constantly striving to make our tools very user-friendly. We are not just focused on creating the dashboard, but having the analytics behind the solution.

Data privacy and security are major concerns with organizations these days. More and more the power of analytics is shifting towards users. There is lot of unstructured data coming from social space and sensors. Organizations want to monetize all this data and create new markets. Data strategy is being talked about on board levels now. According to EIU, companies with good data strategy perform better financially. In public sector, this could be used for various citizen services like providing better healthcare, in Telecoms this is used to do more personalized marketing. Even traditional markets are utilizing analytics  to optimize the readiness of assets. All this tremendous activity in the data space makes Cybersecurity more relevant than ever.

Big data predictive analytics architectures are changing/shifting beyond just data lakes. How is SAS evolving here compared to Teradata, CloudEra or HP?

In the past couple of years, with the onset of the data explosion coupled with cost efficient storage and incremental compute capability, we have seen a shift in focus from pure storage of data to looking at analytical consumption downstream.
Given our deep analytical roots built over the last 40 years, we see the intersection of these compute paradigms as an opportunity in analytical based solutions starting to leverage these disparate data sources. We are looking at the onset of an algorithm economy where organizations would be able to apply these analytical algorithms across the enterprise in a repeatable and durable fashion.

From a SAS perspective, we are looking at leveraging the IaaS and PaaS of vendors like HP, Teradata and others build out an analytical framework where we can leverage both unstructured and structured data to power applications like Cyber Security, IoT-based analytics and the next generation of analytics which will feed these new classes of citizen data scientists.

On average, between 60% and 73% of all data within an enterprise goes unused for analytics, according to research. How do your solutions help in resolving this and how can organizations be better at using more data for analytics?

The challenge today is the foundation of collecting this data. Many organizations do not know the proper way of doing it and structuring the oncoming data. That is where SAS comes in with its data management capability. We always start with end in mind. Organizations need to know what is the business problem that they are trying to solve. There are many ways to data structuring. Organizations have lot of silos, and those silos have there own data strategy and this data is not maximized for cross-selling.

There is an observation that advanced analytic tools remain shelfware. Why is that?

Probably, there is some truth to it. The power of analytics now lies not only with the IT team, but with anybody. We sell our solution subscription-based and our customer care is unique to that particular country. We make sure that they are using the solution correctly. We have a very high percentage of renewal. The possibilities with IoT, Smart cities,  driverless cars etc. is tremendous. Digital marketing is going to grow bigger especially in Telcos and BFSI. Idea Cellular is a good example.

Ensuring good data quality is a must for good data strategy. Govt. Of Maharashtra in UID project  took care of data quality, when it came to taking care of de-duplicating names. Maharashtra can be written in different ways. There were 650 variations of the same name, which they had to standardize.