Modernizing the Analytics Data Pipeline
Webinar Speaker: James Kobielus, Senior Research Director, Data Management
Date: Tuesday, March 22, 2022
Time: 9:00 a.m. PT, 12:00 p.m. ET
Enterprises run on a steady flow of best-fit data analytics. Robust processes ensure these assets are always accurate, relevant, and fit for purpose.
Increasingly, organizations are implementing these processes within structured development and operationalization “pipelines.” Typically, analytics data pipelines include data engineering functions such as extract, transform, and load (ETL) and data science processes such as machine-learning model development.
To make the most of their investments in analytics and data, organizations must continue to modernize these pipelines. Join TDWI’s senior research director James Kobielus to explore how forward-looking businesses build agile, scalable, and manageable analytics data pipelines. He will discuss such key strategies as:
- Automating data engineering and data science workflows for greater scalability, repeatability, consistency, and transparency
- Accelerating data preparation, model training, and other pipeline workloads through real-time replication and change data capture
- Augmenting the productivity of data management and analytics teams through investments in data catalogs
- Migrating data to data lakehouses, distributed data meshes, virtualized data fabrics, and other cloud-based pipeline environments
Product Marketing Director
At Qlik, Anand Rao is a product marketing director for Qlik Data Integration. Anand has 20+ years of experience in data management, working with Informatica, Pentaho (at Hitachi), IBM, and Embarcadero. Before his marketing roles, Anand worked within engineering, developing data integration software. Anand lives near San Francisco and relishes being enveloped by technology.