SQL in the Data Intelligence Platform
1. SQL in the Data Intelligence Platform
Hello! In this video, we will discuss Databricks SQL and how this platform feature fits into your data architecture.2. Lakehouse for all workloads
The data intellifence platform architecture was created not just for advanced AI applications, but for data warehousing workloads as well. Traditionally, these workloads are for SQL queries or Business Intelligence reports critical for business operations and have been supported by separate data warehouses. Let's take a deeper look into how SQL workloads can work in the Data Intelligence Platform.3. Databricks for SQL Users
For the Databricks Data Intelligence platform, these use cases are satisfied by Databricks SQL. Databricks SQL brings a familiar and powerful data warehouse into the lakehouse. To further enhance these warehousing capabilities, Databricks has optimized the compute performance for SQL workloads with an engine called Photon. Photon allows for the second-latency that SQL users have come to expect. Users can use Databricks SQL directly in the platform or connect it to their favorite Business Intelligence tool like Power BI or Tableau. The best part? This comes built into the platform directly! No additional configuration is needed.4. SQL in the Data Intelligence Platform
To put this all in perspective, let's look at the medallion architecture, which provides a high-level overview of how data goes from raw to an analytics-ready dataset. SQL is a great language choice for working with structured data, and can be used throughout this data transformation process. This could mean cleaning and joining data going into the Silver layer, or running reports off the Gold layer of data, as a couple examples.5. SQL in the Data Intelligence Platform
Having the capability for SQL workloads unlocks several benefits for your ecosystem. Since Databricks SQL is fully integrated into the platform, satisfy BI needs as well as working with the other data personas in the platform, such as data engineers. Analysts will benefit from having incredibly scalable and high performing compute clusters, designed for SQL workloads, and all within a familiar user interface. Databricks SQL is different from other data warehousing platforms in a couple key areas. Firstly, Databricks SQL is based on ANSI SQL, which is an open source standard for the SQL language, and one that integrates with many other services. Within Databricks analysts will get enhanced compute power with the additional Photon engine, and can even create visualizations or dashboards directly in the platform. Here we have a few examples of how users can write queries in Databricks. This first query shows that users can access data within a file or directory of files, without even needing to do prior transformation. If one has created a table within Unity Catalog, then this second query shows how to leverage that data. Finally, this third query shows how to leverage the CTAS pattern within ANSI SQL if you are creating new tables.6. Let's review!
With that, let us review some of the main concepts surrounding Databricks SQL.Create Your Free Account
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