Interview with Jennie Wang, Software Engineer, Intel - Speaker at 5th Annual Global Big Data Conf Posted on : Jul 24 - 2017

We feature speakers at 5th Annual Global Big Data Conference - August 2017 to catch up and find out what he or she is working on now and what's coming next. This week we're talking to Jennie Wang, Software Engineer, Intel (Topic : Distributed Deep Learning At Scale On Apache Spark With BigDL)

Interview with  Jennie Wang

1.  Tell us about yourself and your background.
I am senior software engineer in Intel Big Data Technologies organization focusing on machine learning/deep learning on Apache Spark. Previously I was developing large scale event system and services.

2.  What have you been working on recently?
Recently, I am working on the BigDL, which is a Deep Learning framework on Spark. I am engaged in developing of BigDL and consulting and assisting customers to leverage BigDL in their data analytics application.

3.  Tell me about the right tool you used recently to solve customer problem?
We use BigDL, also with other Spark libraries like Spark SQL, MLLib, accompanied with pandas, scikit-learn, numpy, etc.

4.  Where are we now today in terms of the Big data, and where do you think we’ll go over the next five years?
Big data now is adopted to more and more areas. The trend for the future is combining with machine learning/deep learning in big data analytics.

5.  You’ve already hired Y number of people approximately. What would be your pitch to folks out there to join your Organization? Why does your organization matter in the world?
Intel invested a large amount of effort to Hadoop/Spark Community. Intel is a leading contributor to the Apache Spark project, is pioneering the creation of a highly optimized foundation built on the Intel architecture for large-scale distributed analytics with Hadoop/Spark. We invite talents to join our organization to create optimization and innovation on big data area.

6.  What are some of the best takeaways that the attendees can have from your talk on "Distributed Deep Learning At Scale On Apache Spark With BigDL"?
Learn how to makes deep learning more accessible to big data users and data scientists, and easy customer and developer experience  and efficient scale out leveraging Spark architecture.

7.  What are the top 5 Big data Use cases in enterprises?
Fraud Detection, Customer analytics and Prediction, Business Process, Import Healthcare and medicine analytics, Internet of Things.

8.  Which company do you think is winning the global Big Data race?
Many companies are doing very interesting things right now, including Databricks, Cloudera, Microsoft, Facebook, Google etc. Many startups also get achievements in various aspects. It’s hard to tell which one would win.