A data organization leader is upset about the data analysis team’s reports being different from the data engineering team’s reports. The leader believes the siloed nature of their organization’s data engineering and data analysis architectures is to blame.
Which of the following describes how a data lakehouse could alleviate this issue?
A . Both teams would autoscale their work as data size evolves
B . Both teams would use the same source of truth for their work
C . Both teams would reorganize to report to the same department
D . Both teams would be able to collaborate on projects in real-time
E . Both teams would respond more quickly to ad-hoc requests
Answer: B
Explanation:
A data lakehouse is a data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data12. By using a data lakehouse, both the data analysis and data engineering teams can access the same data sources and formats, ensuring data consistency and quality across their reports. A data lakehouse also supports schema enforcement and evolution, data validation, and time travel to old table versions, which can help resolve data conflicts and errors1.
Reference: 1: What is a Data Lakehouse? – Databricks 2: What is a data lakehouse? | IBM
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