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Interview: Andrew Duguay, Prevedere on the Hidden Value in Global Data Sets


We discuss the challenges in analyzing global economic datasets, impact of Big Data growth on economics, desired skills in data scientists, and more.



Twitter Handle: @hey_anmol

andrew-duguayAndrew Duguay is a Senior Economist & Data Scientist with Prevedere Software. Prevedere is a Big Data Predictive Analytics solution that helps companies increase profits and outperform competition by automating the analysis and identification of leading external drivers that improve forecast accuracy.

Andrew graduated from Gordon College with a degree in Economics. He has received a Certificate in Professional Forecasting from the Institute for Business Forecasting and Certificates in Economic Measurement, Applied Econometrics, and Time-Series Analysis and Forecasting from the National Association for Business Economics. He is also co-owner of a small business in central New Hampshire where he resides.

First part of interview

Here is second part of my interview with him:

Anmol Rajpurohit: Q7. What are the most underrated challenges of collecting and analyzing economic datasets?

Andrew Duguay:Many Prevedere users say that having access to1.5 million data sets in a single repository is worth the subscription alone. Businesses often find it challenging to continually download, update and keep on top of the data-integrationmany data releases by the scores of organizations that publish economic datasets in different formats. The data collection process in itself is an underrated challenge, and the consolidation effort of having Prevedere store and update key economic variables for a company can help save time and money.

Another underrated challenge is the ability to efficiently parse through Big Data to find meaningful results. Having global data sets at your fingertips is one thing, it is another thing to be able to make meaningful and highly accurate predictive models based on that data. The tools in our software are specifically aimed at helping the business analyst user to efficiently parse through the mountains of economic data to find the dozen or so economic indicators that are most important to their company.

AR: Q8. How has the rapid growth of Big Data impacted the field of economics? What are the top opportunities and challenges?

AD: Economists now have more data than ever to analyze and big-data3make informed judgments on. This has created unprecedented opportunities in our field for bringing value and improved decision making to businesses through interpretation of the data. However this is also the greatest challenge for economists today; harnessing the insights of all this data. This is why tools like Prevedere are created. Old methods of analysis are no longer good enough and advanced computing is needed to handle the volume of data out there and create meaningful results.

AR: Q9. What is the best advice you have got in your career?

AD: Be humble. Ask questions. Listen.

AR: Q10. Which of the current trends in Big Data arena are of great interest to you? Why?

data-collectionAD: I am very interested in the increasing amount of data that websites such as Google and Zillow are collecting that, when aggregated, can meaningfully measure consumer habits and trends. Prevedere works with some of these relatively new sources and clients are finding ways to improve forecast accuracy by incorporated these measures.

AR: Q11. What key qualities do you look for when interviewing for Data Science related positions on your team? business-understanding

AD: A good Data Scientist will not only have an analytical mind with a statistics and math background but also be able to understand basic business principles. Big Data only becomes useful when a business can make an informed decision based on the analysis that leads to benefits for the company.

AR: Q12. What was the last book that you read and liked? What do you like to do when you are not working?

AD: Ahead of the Curve, by Joseph Ellis. Mr. Ellis was a ahead-of-the-curveleading retail analyst for Goldman Sachs for many years. His ideas about how to look at leading indicators to predict the retail market presented in the book inspired some of the methodology that Prevedere Software uses in its predictive modeling. In full disclosure Mr. Ellis is also an investor and advisor in Prevedere, and we are lucky to be able to leverage his insights and experience.

anmol-rajpurohitAnmol Rajpurohit is a software development intern at Salesforce. He is a former MDP Fellow and a graduate mentor for IoT-SURF at UCI-Calit2. He has presented his research work at various conferences including IEEE Big Data 2013. He is currently a graduate student (MS, Computer Science) at UC, Irvine.

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