Building the Backend: Data Solutions that Power Leading Organizations

Your data team should not just be keeping the lights on, but should be building and creating data products to support the business. In this episode we speak with Murali Bhogavalli a data product manager and explore what is a data product manager and how they differ from a traditional product manager.

Below are the top 3 value bombs:

1. Data should be looked at as a product and treated as such within the organization (i.e. agile methodologies, continuous improvement…)
   
2. Organizations need to be more than just data driven but also data informed. For that to happen, you need to build data literacy into your ecosystem by helping everybody understand what the data means and where is it coming from and the quality of it..
   
3. Product managers typically use data to deliver the outcomes. But for a data PM, data is the deliverable and it also the outcome.

In this episode of Building The Backend we hear from Mark Grover founder @ Stemma, co-creator of Amundsen. Stemma is a fully managed data catalog, powered by the leading open-source data catalog, Amundsen.

Below are top 3 value bombs:

• Automated data catalogs are critical to help wrangle the growing data across organizations. (i.e. Being able to identify out of 150 columns on this table only 10 are being used downstream)
• Tribal knowledge and context cannot be automated - data catalogs cannot be 100% automated.
• Amundsen is an open-source data catalog originally created at Lyft. Stemma has created a managed version of Amundsen.

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In this episode, we speak with Lior Gavish, the co-founder of Monte Carlo to explore all things data quality. Monte Carlo is a data lineage and observability tool that lowers your data downtime.
Top 3 Value Bombs:

1. Data products should be thought of in it’s entirely from the source to the consumer.
2. No one data stakeholder can solve data quality issues, it’s a collaboration of the data engineers, business, data consumer and even software to help automate certain aspects of cataloging and capturing meaningful metadata.
3. Good data quality processes should alert you to anomalies in your metrics before your data consumers do.
   

In this episode, we speak with Raghu Murthy. He is the founder of Datacoral, which provides serverless architectures that support data pipelines and orchestration to facilitate ELT into your Data Warehouse. Prior to founding Datacoral he was at Yahoo, Facebook and was part of the initial team that developed Hive. In this episode we will explore the best patterns for ingesting operational data into your data warehouse, creating metadata first architectures and the role Datacoral serves.

Top 3 Value Bombs:

1. If you're migrating relational data that supports CDC, you should be using CDC to migrate it for the majority of use cases.
2. ELT/ETL pipelines should be orchestrated by a metadata first style architecture.
3. Consumers of the DW, should be notified if data is incomplete.

Welcome to the Building the Backend Podcast! We’re a data podcast focused on uncovering the data technologies, processes, and patterns that are driving today’s most successful companies. In this trailer episode, you will get a glimpse of what to expect with episodes on the show.