Data Pipelines for Data-Driven Apps

WebbMason Analytics (WMA) is a data science company. Our expertise centers around how to collect, transform, and analyze data, then deliver actionable insights in the form of data-driven apps. This talk will discuss some of our key methods and how they are incorporated into the data pipelines and data apps that we deliver, including data integration, data cleansing and validation, and predictive modeling. We will discuss two use cases from recent customers.

The first use case is from a large-scale public transportation company. Using the customer’s internal infrastructure, WMA delivered a set of data-driven apps that enabled government agencies to understand and predict the traffic running through a transportation network.

The second use case comes from WMA’s work with a professional development organization. WMA developed a predictive model used to assign a churn probability to all members of the organization. In this case, WMA used their Analytics Platform to deploy the model through a data-driven app that marketers could use to build targeted lists to support campaigns aimed at reducing churn.

We will show a demonstration of how we use DSS to manage and execute our data pipelines.

Speakers: Michael Lang and Kristen Hardwick

Michael Lang

Michael Lang joined WebbMason Analytics in the fall of 2015 as a Principal Project Manager. In addition to working with customers to ensure successful project delivery, Michael serves as Product Manager for WMA’s Analytics Platform. Prior to joining WMA, Michael was a product manager at Teradata, which acquired his previous company, Revelytix. Michael was VP of Sales Engineering at Revelytix at the time it was acquired. Michael graduated from the University of Maryland - College Park with a B.S. in Mathematics.

Kristen Hardwick

Kristen Hardwick has been working in parallel computing environments in the private, public, and government sectors since 2007. As VP of Big Data Solutions at WebbMason Analytics, her focus is on scoping, designing, and developing Big Data analytics for the Hadoop ecosystem. Kristen has earned both a Bachelor of Science degree and a Master’s degree in Computer Science from Clemson University.