Summary

Data management is hard at any scale, but working in the context of an enterprise organization adds even greater complexity. Infoworks is a platform built to provide a unified set of tooling for managing the full lifecycle of data in large businesses. By reducing the barrier to entry with a graphical interface for defining data transformations and analysis, it makes it easier to bring the domain experts into the process. In this interview co-founder and CTO of Infoworks Amar Arsikere explains the unique challenges faced by enterprise organizations, how the platform is architected to provide the needed flexibility and scale, and how a unified platform for data improves the outcomes of the organizations using it.

Announcements

• Hello and welcome to the Data Engineering Podcast, the show about modern data management
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• Your host is Tobias Macey and today I’m interviewing Amar Arsikere about the Infoworks platform for enterprise data operations and orchestration

Interview

• Introduction
• How did you get involved in the area of data management?
• Can you start by describing what you have built at Infoworks and the story of how it got started?
• What are the fundamental challenges that often plague organizations dealing with "big data"?
  • How do those challenges change or compound in the context of an enterprise organization?
  • What are some of the unique needs that enterprise organizations have of their data?
• What are the design or technical limitations of existing big data technologies that contribute to the overall difficulty of using or integrating them effectively?
• What are some of the tools or platforms that InfoWorks replaces in the overall data lifecycle?
  • How do you identify and prioritize the integrations that you build?
• How is Infoworks itself architected and how has it evolved since you first built it?
• Discoverability and reuse of data is one of the biggest challenges facing organizations of all sizes. How do you address that in your platform?
• What are the roles that use InfoWorks in their day-to-day?
  • What does the workflow look like for each of those roles?
• Can you talk through the overall lifecycle of a unit of data in InfoWorks and the different subsystems that it interacts with at each stage?
• What are some of the design challenges that you face in building a UI oriented workflow while providing the necessary level of control for these systems?
  • How do you handle versioning of pipelines and validation of new iterations prior to production release?
  • What are the cases where the no code, graphical paradigm for data orchestration breaks down?
• What are some of the most challenging, interesting, or unexpected lessons that you have learned since starting Infoworks?

Contact Info

• LinkedIn

Parting Question

• From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

• Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used.
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Links

• InfoWorks
• Google BigTable
• Apache Spark
• Apache Hadoop
• Zynga
• Data Partitioning
• Informatica
• Pentaho
• Talend
• Apache NiFi
• GoldenGate
• BigQuery
• Change Data Capture
  • Podcast Episode About Debezium
• Slowly Changing Dimensions
• Snowflake DB
  • Podcast Episode
• Tableau
• Data Catalog

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA