Infinite Lambda invites you to their event

Tackling time-crime of late-arriving data with dbt

About this event

Join Infinite Lambda and the HCMC Data Meetup group for a webinar.

On Saturday, 9 December, senior analytics engineer Thu Huynh will talk to us about late-arriving data and the ways to handle it in dbt.

Late-arriving and correction-record data are the cheeky culprits for compromising the data quality in your data platform. If you are looking for a way to keep your neat historical tables safe from their harm, join this session and learn how to do it with dbt.


👋🏼 About the speaker

Thu Huynh is a senior analytics engineer at Infinite Lambda with more than 6 years of experience in Business Intelligence, primarily focusing on the retail and e-commerce industries.

Thu started her journey in the field as a data analyst with an ever-increasing eagerness to find insights to help businesses grow through them. She gradually developed an interest in applying engineering best practices to streamline and scale analytics work, which brought her straight to analytics. Thu is certified in Tableau, Looker, dbt and Snowflake, and she leverages the modern data stack to deliver value to organisations.


🙌🏼 Who is this event suitable for?

  • Current dbt users who want to build on their skills;
  • Engineers new to dbt who want to see how they can leverage the tool;
  • Data professionals looking to expand their expertise in data quality;
  • People who are about to start their career in data and want to understand more about the work of analytics engineers;
  • All data enthusiasts.


📍 Are you based in HCMC?

Come join us in-person at Infinite Lambda's office:

6th floor, ABTEL TOWER, 36 Phan Dang Luu Street

Ward 6, Binh Thanh District

Ho Chi Minh City, Vietnam

Hosted by

  • Team member
    OT T
    Oanh Tran

  • Team member
    CK T
    Chau Kim Minh le

Infinite Lambda

Engineering that empowers people

Infinite Lambda is a global data and AI consultancy and academy.

We help top organisations build cutting-edge data capabilities across the value chain — from fast data use cases, such as intelligent apps, ML & GenAI, to the more deliberate, slow data use cases, such as analytics and data science.