Expert Panel Discussion: How DataOps is Adding Value to Data Lakes

June 6, 2019
10:00 am (PT)
1:00 pm (ET)


Storm Insight

About the Webinar

The terms big data and data lakes definitely have the potential to shake up the technology world, but many questions remain around how to leverage them for maximum business value.

Join us for an interactive webinar featuring Alex Gorelik, best-selling author of“The Enterprise Data Lake, Delivering the Promise of Big Data and Data Science”, Joe Hellerstein from Trifacta and Girish Pancha from StreamSets as they share DataOps best practices for building a successful data lake. Through experience with hundreds of Big Data practitioners, they will share how companies can leverage DataOps to provide a foundation for insightful data science and self-service analytics and explore the components of a successful data lake and some of the little known reasons for failure.

During the webinar you can expect to learn:

  • How forward-looking companies are using various technologies to create greater business value
  • New trends in big data/data lakes
  • The evolving role of the DataOps team
  • Components of a successful data lake
  • Why some big data initiatives fail

  • Webinar Details:

  • What: Live webinar: How DataOps is Adding Value to Data Lakes
  • Featured Speakers:

    • Alex Gorelik, CTO and Founder of Waterline Data
    • Joe Hellerstein, Co-Founder and CSO of Trifacta
    • Girish Pancha, Co-Founder and CEO of StreamSets
  • When: Thursday, June 6 10:00 AM PST

The Experts

Alex Gorelik
Alex Gorelik
Waterline Data CTO and Founder

Alex Gorelik is the founder and CTO of Waterline Data, a startup focused on enhancing the value of modern data lakes through data self-service and governance. Alex is a serial entrepreneur and innovator who has spent over 25 years inventing and bringing to market cutting-edge data-oriented technology. Prior to Waterline, Alex was an EIR at Menlo Ventures, GM of the Data Quality Business Unit at Informatica, and an IBM Distinguished Engineer for the IBM Infosphere team.

ODSC Webinar Calendar

May 30th, 2019
1 pm – 2 pm EST
Click here to register


Storm Insight

About the Webinar

In this session, attendees will learn how the OmniSci GPU-accelerated SQL engine fits into the overall RAPIDS partner ecosystem for open-source GPU analytics. Using open bike-share data, users will learn how to ingest streaming data from Apache Kafka into OmniSci, perform descriptive statistics and feature engineering using both SQL and cuDF with Python and return the results as a GPU DataFrame. By the end of the session, attendees should feel comfortable that an entire data science workflow can be accomplished using tools from the RAPIDS eco-system, all without the data ever leaving the GPU.

Topics to be highlighted:

  • What is RAPIDS? (discussion of NVIDIA open-source RAPIDS project, how it relates to Apache Arrow, etc.)
  • What is OmniSci and how does it fit into the RAPIDS eco-system
  • Example:
  • Ingesting a data stream from Apache Kafka into OmniSci
  • Using pymapd (Python) to query data from OmniSci and do basic visualizations
  • Use cudf to do data cleaning and feature engineering
  • Show how cudf dataframes can be passed to machine learning libraries like Tensorflow, PyTorch or xgboost.

The Experts

Alex Gorelik
Alex Gorelik
Senior Developer Advocate at OmniSci

Randy Zwitch is a Senior Developer Advocate at OmniSci, enabling customers and community users alike to utilize OmniSci to its fullest potential. With broad industry experience in Energy, Digital Analytics, Banking, Telecommunications and Media, Randy brings a wealth of knowledge across verticals as well as an in-depth knowledge of open-source tools for analytics.

ACAMS Training: Free Webinars

May 2, 2019
12:00 – 1:00 PM ET


Storm Insight

About the Webinar

In this insightful session, Brendan Brothers, Co-Founder of Verafin and Anti-Financial Crime Specialist, will discuss the evolution of financial crime and how financial institutions can embrace innovative approaches to proactively prevent fraud and combat crime ring activity.

Industry experts will outline how financial institutions can leverage big data, machine learning technology and 314(b) information sharing for effective fraud prevention, including proactive trend identification, reduction in false positive results, and collaborative investigations of multi-institutional crime ring activity.

Learning Objectives

  • Understand the limitations and challenges of conventional fraud prevention approaches
  • Leveraging big data, machine learning technology, and 314(b) information sharing to mitigate losses and prevent fraud
  • Enhancing detection, strengthening investigations, and improving reporting to law enforcement

Who Should Attend

  • Compliance Personnel
  • General Counsel
  • Industry Consultants


  • Financial Institutions
  • Fraud Detection
  • Global

The Experts