|
-
1)What are the database activities on data warehousing ?
2)Knowing all the things is good but As a dba what are all should be known to maintain data warehouse ?
J Gangadhar
-
-
Here's also an excellent article about data warehouse - https://www.cleveroad.com/blog/enter...data-warehouse
-
A data warehouse is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially analytics. Data warehouses are solely intended to perform queries and analysis and often contain large amounts of historical data. The data within a data warehouse is usually derived from a wide range of sources such as application log files and transaction applications.
-
Database activities in data warehousing primarily involve data extraction, transformation, and loading (ETL) processes, data storage, data retrieval, and data analysis. ETL operations are essential for moving data from source systems to the data warehouse, while storage and retrieval support efficient data management and access. Data analysis includes querying, reporting, and data mining to derive valuable insights.
As a database administrator (DBA) responsible for maintaining a data warehouse, one should have expertise in ETL tools, data modeling, SQL, performance optimization, and security measures. xx
Last edited by Steve R Jones; 12-12-2023 at 04:31 AM.
-
Database activities in data warehousing typically include data extraction from multiple sources, transformation and cleaning (ETL/ELT), loading into staging and warehouse layers, indexing and partitioning for performance, aggregation for reporting, and ongoing data quality checks. You also deal with query optimization, historical data management, and sometimes real-time or near-real-time data ingestion depending on the architecture.
For a DBA maintaining a data warehouse, it?s not just about traditional database administration. You need strong knowledge of performance tuning (especially large-scale queries), storage management, backup and recovery strategies for large datasets, schema design (star/snowflake models), and ETL pipeline monitoring. It?s also important to understand workload management, concurrency issues, and cost/performance trade-offs in cloud environments if the warehouse is cloud-based.
Beyond the technical layer, a big part of the role is ensuring that data flows reliably between systems and that failures are detected and resolved quickly. In modern setups, this often means thinking in terms of end-to-end data workflows rather than isolated database tasks. That?s where workflow design and automation concepts become relevant, since the warehouse is only as reliable as the processes feeding it ?
Posting Permissions
- You may not post new threads
- You may not post replies
- You may not post attachments
- You may not edit your posts
-
Forum Rules
|
Click Here to Expand Forum to Full Width
|
Reply With Quote