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Data scientists a “currency for transformation”

Zafirah Salim | Feb. 2, 2016
To have a better understanding of this 'sexy' job, I spoke to Vivek Gupta, Microsoft's senior data scientist and Vivek Ravindran, Director, Data Insights Lead, Microsoft Asia Pacific, to get an insight into what a data scientist actually does, and why they are increasingly crucial in an organisation.

When it comes to data collection, many organisations are concerned with the data quality, according to Gupta. Again, this explains why data scientists spend the bulk of their time doing data cleansing.

He also noted that although many companies have been collecting data for many years, they are unfortunately "not reacting to it fast enough."

"Companies do have some existing data, but they tend to look at it horizontally - all they end up doing is producing Powerpoint slides that goes in some report. They are not able to react on the data on a regular basis. They need to be able to speed up that execution with real actions in real-time rather than wait every quarter," said Gupta.

Ravindran added that the paradigm is now changing. He feels that organisations are not thinking about the answers, but the right questions to ask.

"If you don't have a data scientist, chances are you don't know what you should know, so you don't know what are the right questions to ask," he said. "Even if you don't have the right data now, you can start by formulating the right questions and work on developing a strategy about the right data."

Data scientists are also crucial for small-sized businesses, including startups, Ravindran emphasized. A startup may not have a large data science organisation, but at least they are able to partner with another company that can provide that little bit of knowledge and insight to create something which they can use.

For instance, Fujitsu has partnered with a farmer to implement a connected cow project, which leverages cloud computing, wearable technology and the Internet of Things to help farmers accurately predict the best time to get their cows pregnant.

Called Gyujo, the system was developed by Fujitsu and uses a pedometer strapped to the leg of the cow to figure out the best time to inseminate a cow. The time and movement data can help farmers not only monitor the general health of cattle, but also track when cows are going into estrus (a condition more commonly known as "in heat").

The system detects spikes in movement activity at night this serves as an indication that the cow is going into estrus and is ready for artificial insemination. Artificial inseminate success rates today are around 70 percent with a pregnancy rate of around 40 percent when the detection rate of when the cow is in heat is 55 percent. If the detection rate is pushed up to 95 percent, then the pregnancy rate shoots up to 67 percent.


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