Webinars

Predicting TV Tune-In Using PySpark, MLlib & Delta Lakehouse

At MIQ Digital India Pvt. Ltd. we collect and process high-volume TV viewing data and apply machine learning models to help TV networks get the maximum value out of their ad slots.

We use Apache Spark MLlib to model and PySpark for data wrangling and feature engineering with a Kafka-based event-driven microservices architecture. It uses a well-defined data engineering ecosystem of a lakehouse architecture built on top of Delta Engine.

This talk will cover scaling MiQ’s TV product to market across >50 advertisers, details of pipeline optimization for data at TB scale, and cost optimizations for model generations and prediction.

Download PDF

Ready to Get Started? Here Are Some Resources to Help

Whitepaper

2024 State of the Data Lakehouse

Benchmark your organization with Dremio's State of the Data Lakehouse Survey Report!

read more

Expert Panel Discussion – Data Integration Trends and Best Practices Webinar

TDWI senior research director James Kobielus will engage data industry experts in an in-depth discussion of data integration trends and best practices

read more
OctotronicDremio Smart Data Smart Factory 1

Webinars

Smart Data – Smart Factory with Octotronic and Dremio

Wie bringt ein Data Lake House die Smart Factory auf ein neues Level?

read more
get started

Get Started Free

No time limit - totally free - just the way you like it.

Sign Up Now
demo on demand

See Dremio in Action

Not ready to get started today? See the platform in action.

Watch Demo
talk expert

Talk to an Expert

Not sure where to start? Get your questions answered fast.

Contact Us