7 ways data science is changing business

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Today, organizations are applying data scientists to a number of sectors to help make smarter decisions for engaging customers and allocating resources.

Following are the 7 most powerful  questions about data science by Navin Manaswi, Chief data scientist at Mantra AI

1. Why do business leaders need data science to accelerate their business growth?

Due to large volume of data coming from various sources in various formats at various points of time, traditional business intelligence does not meet the needs of business leaders.

Business problems can range from minimizing the transportation cost in a given network to the finding the best recommendation engine for their various kinds of customers.
Even traditional knowledge of customer segmentation, building prediction models, building classifiers sound to be not- so-good solutions.

2. Can you explain how data scientists help big companies solve big problems?

Data scientists, in big companies like Adidas, General Mills, Snapdeal and Vodafone, solve their own business problem and help them strategize and grow fast in the fast-changing competitive business world. They aim to delight their customers, to automate various business processes and to better decision making processes by discovering the hidden insights/patterns.

For example, if right discounts/coupons are given to the right set of customers at the right time, the company makes a lot of money. Data science help e-commerce companies like Flipkart recommend right item to the e-customers and then significantly increase the revenue.

3. In the wake of the smart city initiative, do you think it is imperative to have a data scientist for government of India?

US and Singapore government have already appointed the Chief Data Scientist to help them in decision making process. India should not lag as it needs to address aspiration of billions of people. Data Science would certainly improve policy of education, healthcare, finance, industry, agriculture and other sectors in addition to smart city initiative and eventually bring efficiency of government functionaries and activities. In other words, data science in government is being used to provide decision/policy makers with analytical insights from huge volumes of structured and unstructured data.

4. How can a data scientist help government tackle some of the big problems and improve governance?

Data would be sourced from census data as well as surveys, social media and big data scraped from the web. Once data is collected, it would go through data preparation and data modelling stages before we would make a useful benchmarking, prediction and prescription. It will be helping government understand and tackle some of the key problems of people. The output of data science initiative will be the significant improvement in performance of government services, the potential impact of new policies and government’s financial status.

In short, the vision is to create nationwide data policies that improves operational and functional guidelines and forward-leaning practices to advance our nation’s leadership in the data age

5. What are some of your responsibilities that you do on a daily basis? And what tools do you use to handle data?

Identification of the right data sources, data collection, cumbersome data preparation followed by building of anyon of predictive models, recommendation engine, classifier, customer segmentation engine, sentiment analysis engine, face/voice recognition engine, forecasting models are some of my responsibilities which I do on a daily basis. Presenting all the mentioned models and insights to the most senior business leaders in their own language is one of the most favourite responsibilities of data scientists.

6. What are some of the typical challenges that you face as a data scientist?

Sourcing the relevant data from the right sources and then making it consistent and useful has been always a daunting task. Utilising complex unstructured data like Forum posts for our data modelling purposes has been another daunting task. That is why Natural Language Processing (NLP) has been a hot research area of data science. I always need to recall myself that I belong to pure data science as much as I, to business world as one pushes towards introversion but another, towards extraversion.

7. What do you like to suggest to aspiring data scientists?

Data science is nothing less than an ultimate fun. You would acquire a unique perspective on the business, the government and the life in very holistic and exceptional way. Road to data science may seem to be tough but it is worth going for. If you love to explore anything of programming, mathematics, statistics and business needs, you should keep participating in and exploring blogs, articles, forums focused on R or python or data science. Following the right blogs & articles and practicing codes sound to be the fastest and the best way to become a data scientist.



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