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I am preparing for the data analyst exam and I need as many resources as I can get to fully prepare. Hands-on labs will be welcome as well

boyelana
Contributor III

โ€Ž12-06-2022 07:45 AM

I am preparing for the data analyst exam and I need as many resources as I can get to fully prepare. Hands-on labs will be welcome as well

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9 REPLIES 9

Hubert-Dudek
Esteemed Contributor III

โ€Ž12-06-2022 08:01 AM

Please check the data analyst path on Academy https://customer-academy.databricks.com/learn/lp/78/data-analyst-learning-plan

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Rishabh264
Honored Contributor II
In response to Hubert-Dudek

โ€Ž12-06-2022 11:42 AM

yes refer the databricks documentation , you will easily get the proper learning plan

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Aviral-Bhardwaj
Esteemed Contributor III
In response to boyelana

โ€Ž12-10-2022 07:30 AM

this is amazing ,thanks

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UmaMahesh1
Honored Contributor III

โ€Ž12-06-2022 09:15 AM

Best resource is the one databricks training academy is providing. You can clear easily using that alone.

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Ajay-Pandey
Esteemed Contributor III

โ€Ž12-07-2022 01:00 AM

Please refer below topics that may help you in exam-

  • Describe Databricks SQL and its capabilities, including:
    • Databricks SQL (users, benefits, queries, dashboards, compute)
    • Integrations (Partner Connect, data ingestion, other BI tools)
    • Lakehouse (medallion architecture, streaming data)
  • Manage data with Databricks tools and best practices, including:
    • Delta Lake (basics, benefits)
    • Storage and Management (tables, databases, views, Data Explorer)
    • Security (table ownership, PII data)
  • Use Structured Query Language (SQL) to complete tasks in the Lakehouse, including:
    • Basic SQL (basic query structure, combining data, aggregations)
    • Complex Data (nested data objects, roll-ups, windows, cubes)
    • SQL in the Lakehouse (ANSI SQL, working with silver-level data, query history, higher-order functions, user-defined functions)
  • Create production-grade data visualizations and dashboards, including:
    • Visualization (Databricks SQL capabilities, types of visualizations, storytelling with data)
    • Dashboarding (Databricks SQL capabilities, parameterized dashboards and queries, sharing)
    • Production (refresh schedules, query alerts)
  • Develop analytics applications to solve common data analytics problems, including:
    • Descriptive Statistics (discrete statistics, summary statistics)
    • Common Applications (data enhancement, data blending, last-mile ETL)

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