Snowflake for Data Analysts

Build practical Snowflake skills from the foundations to advanced analytics. Learn how to load and validate data, write business-focused SQL, query JSON, build reusable reporting models, and manage query performance, costs, and access. Across nine modules, you will work with consistent retail datasets, clear explanations, worked examples, practice exercises, and interview questions. Explore joins, window functions, customer retention, data quality checks, views, MERGE, Time Travel, tasks, streams, and dynamic tables.

Rutvik Acharya

Principal Data Scientist

Atlassian

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What You'll Learn

Load, structure, and validate data using Snowflake tables, stages, file formats, and COPY INTO.

Answer business questions using joins, CTEs, window functions, cohort analysis, and JSON queries.

Build dependable reporting models while managing data quality, query performance, costs, and permissions.

Create repeatable analytics workflows and complete projects covering retail profitability, customer retention, and website conversion.

Who Should Attend

Aspiring data analysts seeking practical experience with Snowflake and SQL.

Data analysts moving from spreadsheets or traditional databases to cloud analytics.

Business intelligence professionals building reliable reporting datasets.

Students and working professionals developing a data analytics portfolio.

CERTIFICATION

Certificate of Completion

9 Modules

20 Hour

38 Lessons

38 Challenges

Language: English

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FAQ

FREQUENTLY ASKED QUESTIONS

The course covers Snowflake foundations, data loading, business SQL, advanced analytical SQL, JSON, data validation, reporting models, performance, cost controls, permissions, and repeatable analytics workflows.

The course is designed for aspiring data analysts, analysts moving from spreadsheets or traditional databases, BI professionals, and learners building a data analytics portfolio.

No prior Snowflake experience is required. The course begins with the platform’s foundations and progresses to advanced analysis and reporting workflows.

The course contains nine modules and 38 lessons, including two complete portfolio projects. The material includes explanations, diagrams, worked examples, practice exercises, and interview questions.

The estimated completion time is 20 hours, including practice exercises and portfolio projects. The course is self-paced, so your actual time will depend on your experience and practice.

You will learn filtering, aggregation, joins, conditional logic, date functions, CTEs, subqueries, window functions, and QUALIFY. You will apply these skills to business metrics, cohort analysis, retention, and deduplication.

Yes. The course covers VARIANT, nested fields, safe value conversion, and FLATTEN. You will also combine website events with customer and order data.

Yes. You will check completeness, uniqueness, validity, and consistency, reconcile revenue, and build reusable reporting models. The course also introduces MERGE, Time Travel, and monitoring data freshness.

The course includes a retail performance and profitability project and a customer retention and website conversion project. Both include business questions, synthetic datasets, complete SQL solutions, and expected results.

Yes. The course includes 36 practice exercises and two portfolio projects, with worked solutions to help you check your reasoning and results.

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