Data Warehousing

Business Intelligence, as we know it today, is impossible without Data Warehousing.

A data warehouse stores data from a company’s operational databases and external sources. Data warehouse platforms are different from operational databases because they store historical information, which makes it easier for business leaders to analyze data over a specific time.

But why is it so important?

Data is extracted on a periodic basis from source systems and moved to a dedicated server that contains the data warehouse. During this process, the data is cleaned, formatted, validated,
reorganized, summarized, and integrated with other sources. BI teams can analyze data in real time to proactively address challenges, identify opportunities, gain efficiency, reduce costs, or proactively respond to business events.

Companies are increasingly moving away from traditional data warehouses to the cloud, leveraging the cost savings and scalability that managed services can provide.

Some primary advantages of data warehousing in the Cloud:
- It’s managed
- It can provide better uptime compared to on-premises data warehouses
- It’s built for scale
- It’s cost effective
- It supports real-time insights
- It supports machine learning and AI initiatives

Earn a skill badge by completing the Build and Optimize Data Warehouses with BigQuery quest, where you will learn how to transform your data warehouse using BigQuery, including how to:
1. Use a command line interface to query and load sample data.
2. Create new reporting tables using SQL, JOINS, and UNIONs.
3. Create dataset partitions that will reduce cost and improve query performance.
4. Create and troubleshoot joins.
5. Load, query, and un-nest semi-structured datasets.
6. Use Data Catalog.
7. And most importantly it will help you get ready for something big coming up soon! 🎁

Use Code: 1q-DWH-22 for free credits!