Visual Analysis and Data Processing in Tableau

Date of Presentation: 
Wednesday, November 18, 2015
2015 Fall
Research Focus: 

Abstract - Data visualization has been experiencing a rapid growth in recent years. An ability to predict and embrace many directions the market is taking greatly contributed to the current strong position of Tableau. An original research project has become a powerful visual framework to perform interactive exploration, reporting and storytelling over data.

In this talk we present how users work on different platforms or in the cloud to perform data modeling, preparation, management and rich analysis including integration with statistical packages and blending across data sets. Furthermore, we will cover the architecture of the data processing layer designed to handle the growing number of users, data volumes and complexity of analysis. Tableau works with a wide spectrum of popular back-ends and offers its own column store when efficient analytic databases are not available. Both approaches require sophisticated pipelines to ensure high interactivity under ad hoc workloads.


Pawel Terlecki is a development manager on the query team at Tableau. His responsibilities include vision, design and implementation of an in-house column store, the Tableau Data Engine and several data processing components. Prior to Tableau he worked on business application, web frameworks, database servers, in particular Microsoft SQL Server, and data mining projects. He holds a PhD in Computer Science from Warsaw University of Technology, with specialization in information systems and knowledge discovery, and BSc in Economics from Warsaw University. He published several works on databases and data mining and is a frequent guest at major conferences in these fields. Building efficient and reliable solutions is his passion.

Patrice Pelland is a Senior Director of the Platform Development at Tableau. He has 20+ years of software engineering and technical leadership experience in areas including agile development, parallel computing, low-level system development, query generation+optimization, caching platforms, highly optimized in-memory columnar data store, web services, scalability, cryptography, developer tools and SDKs, visual analysis, build systems, developer engineering metrics, programming languages, statistics & predictive analysis, and computer graphics. He was also teaching computer science classes in College in Canada for 7 years. He published 5 books on various topics around programming languages.

Pawel Terlecki, Patrice Pelland
Speaker affiliation: 
Tableau Software