Databricks and the Rise of the Data Engineer | #DataManagement #BusinessInsights #Databricks #Shorts

Key Concepts:

• Analytical Data vs. Operational/Transactional Data
• ETL (Extract, Transform, Load)
• Data Lineage
• Business Lineage
• End-to-End Data Ownership
• Data Bricks Ecosystem

Main Argument: The Shift Towards End-to-End Data Ownership

The core argument is that companies are increasingly seeking to own the entire data lifecycle, from creation to consumption, rather than solely focusing on analytical data. The speaker emphasizes that owning analytical data alone is insufficient; the real value lies in controlling the operational or transactional side where data originates.

The Problem with the Traditional Approach

The traditional approach involves extracting data from operational systems (like Salesforce, SAP, or ADP) via ETL processes into analytical solutions like Data Bricks. This creates a separation where analytical platforms are merely recipients of data, not originators.

The Importance of Operational Data

The speaker highlights that the world's most important data resides in operational systems such as Salesforce and SAP. EDP may have the best payroll data. The key is that these systems are where the data is created.

Data Bricks' Strategy: End-to-End Control

Data Bricks wants to own the entire data lifecycle. This means that the data never leaves the Data Bricks ecosystem.

Business Benefits of End-to-End Ownership

The speaker illustrates the business benefits with the example of SEC reporting. Businesses require:

• Data Lineage: Tracing the origin and transformations of data.
• Business Lineage: Understanding how data relates to business processes.
• Transparency: Visibility into the entire data journey.

When Data Bricks controls the entire lifecycle, businesses gain complete transparency and control over their data, from its creation to its use in dashboards and reports.

Conclusion

The speaker concludes that the trend towards end-to-end data ownership is driven by the need for greater control, transparency, and lineage in data management. Companies like Data Bricks are strategically positioning themselves to own the entire data lifecycle, ensuring that data remains within their ecosystem and providing businesses with a comprehensive view of their data assets.