Databricks SQL Analytics Deep Dive for the Data Analyst

In this session, we will cover best practices for analysts, data scientists, and SQL developers exploring Databricks SQL Analytics as a solution for their companies. This guided technical tour of the product walks through:

• Creating and working with queries, dashboards, query refresh and alerts
• Constructing queries for semi-structured data, such as json, structs, and arrays
• Navigating the improved Spark SQL Documentation to find and leverage powerful built-in functions to solve common problems
• Creating connections to 3rd party BI and database tools (PowerBI, Tableau, dbVisualizer etc.)

Connect with us:

[radekou]

Timestamps:
4:00 - demo begins - UI interview
6:35 - data selection, schema etc.
7:09 - select statement
9:10 - visualisation - map
15:39 - bar chart
17:46 - query parameter
20:29 - query-based dropdown
25:12 - creating a dashboard
29:00 - schedule data refresh
29:43 - set up alerts
34:35 - working with "silver" level/array type data
41:50 - handling arrays - transform
46:00 - handling arrays - reduce
51:45 - connecting to 3rd party tools
51:30 - tableau

[angallaamardeep]

this is an excellent lecture I have ever come across, Thank you very much

[basyasalid]

Thank you for sharing the session. This was great and informative!

[dipanjansaha]

Couple of questions
1. Assume I have shared the dashboard link with business users, everytime an user opens the dashboard will spin up the cluster?

2. How about ci/cd pipelines? I.e. how to play/cook my code in dev then move to production?

[dianacarolinaduquemontoya]

I can see that the lady made a mistake writing the average temperatures query and the video was edited with no clarification, this can be confusing.