Getting Up to Speed on Big Data Analytics

Data is being collected everywhere - and from everything. The idea is that it can provide the power of insights never before possible into everything from the patient care to the health of machinery to customer sentiment about products and services. But to reveal these  valuable insights, this data also has to be captured and analyzed in ways never before possible. To help provide training about the world of data science for newcomers as well as those who want to advance their skills, Bart Baesens, professor at KU Leuven (Belgium), lecturer at the University of Southampton (United Kingdom), and Big Data Quarterly columnist, has developed an e-learning version of his course “Advanced Analytics in a Big Data World.”  The training is being offered in collaboration with SAS.  Here, Baesens talks with DBTA about why data analytics education is important now and what this online course seeks to provide.

DBTA: Why is this class needed now? What has changed?

Baesens: Data is everywhere.  IBM projects that every day we generate 2.5 quintillion bytes of data.  In relative terms, this means 90% of the data in the world has been created in the last two years.  Gartner projects that through 2015, 85% of Fortune 500 organizations will be unable to exploit big data for competitive advantage and about 4.4 million jobs will be created around big data.  These numbers are a strong indication of the ubiquity of big data and the corresponding need for analytical skills and resources, because as the data piles up, managing and analyzing these data resources in the most optimal way become critical success factors in creating competitive advantage and strategic leverage.  In this e-learning course, we discuss state-of-the-art analytical techniques to analyze big data.  The course focusses on the concepts and modeling steps, rather than the software.  It is based on more than 15 years of research and industry experience in the field. 

DBTA: Who is it targeted at in terms of responsibilities and expertise/skills?

Baesens: This course basically targets data scientists working in a diversity of settings such as credit risk modeling, marketing analytics (e.g., churn/response modeling, customer segmentation), fraud detection (e.g., credit card fraud, insurance fraud, anti-money laundering), and web analytics.  The course focusses on the key skills of what makes up a good data scientist: quantitative modeling, communication and visualization, as well as creativity.  Although the course is primarily targeted at newcomers who want to get up to speed on data science, it can also be beneficial to seasoned data scientists who want to perfect their modeling skills.

DBTA: Is the training being offered in two ways: actual classroom and e-learning? What does that enable for participants?

Baesens: Yes, that’s right.  We have been teaching the classroom version now for about 10 years all over the globe.  A key benefit of a classroom version is the close interaction between the instructor and students.  However, we have seen that due to busy work schedules, it’s getting more and more difficult for people to stay away from work for 3 days.  Moreover, many firms have also substantially reduced the travel budget, which is really unfortunate from an employee education perspective.  Hence, we decided to come up with an e-learning version of the course.  We recorded the entire course and produced it into movies of about 5 minutes on average.  Upon registration, the participant receives a code which gives him/her access to all videos during 1 year or 365 days.  The videos can be played, replayed, paused whenever and as many times the participant likes.  No specific software is needed.  A laptop, iPad, iPhone, etc., with a web browser is sufficient.  The course also has various quizzes to evaluate the participant’s understanding of concepts discussed.  Upon completion, a course certificate can be printed.

DBTA: Is this the first e-learning course you developed?  What are your experiences and what are your future plans?

Baesens: In fact, it isn’t.  This is our second course.  Our first e-learning course was on the topic of credit risk modeling. Given the positive feedback we received and the lessons learned, we started to develop our second e-learning course on advanced analytics.  Our future plans are to continue along this road.  Most likely our next course topic will focus on fraud analytics, which another topic attracting lots of industry interest nowadays.  We are also continuously updating our YouTube channel, where you can find some free movies discussing our research on analytics.

DBTA: Do you have any advice for aspiring data scientists?

Baesens: Yes, sure! The world is changing at a faster pace than ever before.  Just think about the Internet of Things, drones, self-driving cars, etc.  I believe we are only at the start of the data avalanche.  To spearhead the competition, it is of key importance to continuously educate yourself, understand new technologies and see how they can create added business value. 

Big Data Quarterly is a new magazine and digital resource, from the editors of Database Trends and Applications (DBTA) magazine. Subscribe now.

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