100+ Free SnowPro Advanced Data Analyst Practice Questions

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Question 1

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Which Snowflake function converts a JSON string into a queryable VARIANT?

PARSE_JSON

TO_JSON

OBJECT_CONSTRUCT

ARRAY_CONSTRUCT

to track

2026 Statistics

Key Facts: SnowPro Advanced Data Analyst Exam

Live Exam Questions

Snowflake

115 min

Time Limit

Snowflake

750/1000

Passing Score

Scaled

$375

Exam Fee

$300 in India

32%

Largest Domain

Data Analysis

2 years

Certification Valid

Renew via SnowPro Core

SnowPro Advanced Data Analyst (DAA-C01) is a 65-question Snowflake exam delivered in 115 minutes with a passing scaled score of 750/1000. The official domain weights are Data Ingestion and Data Preparation (17%), Data Transformation and Data Modeling (22%), Data Analysis (32%), and Data Presentation and Data Visualization (29%). Snowflake requires an active SnowPro Core certification as a prerequisite and recommends 1+ year of Snowflake analytics experience plus advanced SQL fluency. Exam fee is $375 USD per attempt ($300 USD in India). Certification is valid for 2 years; renewal requires an active SnowPro Core certification.

Sample SnowPro Advanced Data Analyst Practice Questions

Try these sample questions to test your SnowPro Advanced Data Analyst exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1Which Snowflake function converts a JSON string into a queryable VARIANT?

A.PARSE_JSON

B.TO_JSON

C.OBJECT_CONSTRUCT

D.ARRAY_CONSTRUCT

Explanation: PARSE_JSON parses a JSON string into a VARIANT that you can traverse with the colon path syntax. TO_JSON does the inverse. OBJECT_CONSTRUCT and ARRAY_CONSTRUCT build new objects/arrays.

2Which window function returns the value of the previous row within a partition?

A.LAG

B.LEAD

C.ROW_NUMBER

D.NTILE

Explanation: LAG returns a value from a row at a specified offset before the current row. LEAD returns a row after, ROW_NUMBER returns a sequential rank, and NTILE buckets rows.

3Which Snowflake construct lets you express a recursive query for a hierarchy (e.g., manager-employee)?

A.WITH RECURSIVE CTE

B.RECURSIVE JOIN

C.ALTER VIEW RECURSIVE

D.CONNECT BY

Explanation: Snowflake supports recursive CTEs with WITH RECURSIVE for hierarchical traversal. RECURSIVE JOIN, ALTER VIEW RECURSIVE, and CONNECT BY are not Snowflake syntax.

4Which Snowflake function pivots an ARRAY column into one row per element?

A.FLATTEN with LATERAL JOIN

B.ARRAY_AGG

C.ARRAY_SIZE

D.UNPACK

Explanation: FLATTEN combined with LATERAL produces one output row per element of an ARRAY (or VARIANT array). ARRAY_AGG aggregates rows into an array (the inverse), ARRAY_SIZE returns length, and UNPACK is not a Snowflake function.

5Which Snowflake feature renders an interactive chart inside a worksheet without external BI tools?

A.Snowsight charts

B.SnowSQL

C.ALTER VIEW

D.Stream

Explanation: Snowsight worksheets include a chart panel that visualizes the result set. SnowSQL is the CLI; ALTER VIEW changes a view definition; Stream captures CDC.

6Which command loads a Parquet file from an external stage into a Snowflake table?

A.COPY INTO target_table FROM @stage FILE_FORMAT = (TYPE = PARQUET)

B.INSERT INTO target_table FROM PARQUET

C.LOAD PARQUET

D.SELECT * FROM PARQUET

Explanation: COPY INTO with FILE_FORMAT = (TYPE = PARQUET) loads Parquet from a stage into a target table. The other commands are not Snowflake syntax.

7Which Snowflake feature continuously refreshes a table from a source query with a target lag?

A.Dynamic table

B.Materialized view

C.Stream

D.Resource monitor

Explanation: Dynamic tables are defined declaratively with TARGET_LAG and Snowflake schedules refreshes to keep results within that lag. Materialized views maintain query results but do not orchestrate multi-step pipelines. Streams are CDC; resource monitors govern credits.

8Which window frame returns a 7-day rolling sum partitioned by store?

A.SUM(x) OVER (PARTITION BY store ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW)

B.SUM(x) OVER (PARTITION BY store)

C.SUM(x) GROUP BY store

D.SUM(x) OVER (ORDER BY date ROWS UNBOUNDED PRECEDING)

Explanation: ROWS BETWEEN 6 PRECEDING AND CURRENT ROW yields a 7-row window for the rolling sum. The other options sum over the full partition or do not partition by store.

9Which Snowflake function extracts a numeric value from a JSON path in a VARIANT column?

A.v:price::FLOAT or GET_PATH(v,'price')::FLOAT

B.JSON_VALUE

C.ARRAY_GET

D.TO_JSON

Explanation: Snowflake VARIANT supports the colon path syntax (v:price) and GET_PATH, both with explicit casting. JSON_VALUE is not Snowflake syntax. ARRAY_GET fetches array elements; TO_JSON serializes.

10Which Cortex feature converts a natural-language question into Snowflake SQL given a semantic model?

A.Cortex Analyst

B.Cortex Search

C.Cortex Fine-tuning

D.Document AI

Explanation: Cortex Analyst translates business questions into SQL based on a YAML semantic model. The other Cortex services serve retrieval, fine-tuning, or document extraction.

About the SnowPro Advanced Data Analyst Exam

The SnowPro Advanced: Data Analyst (DAA-C01) certification validates advanced analytics skills on the Snowflake AI Data Cloud. It covers data ingestion and preparation (COPY INTO, Snowpipe, file formats), advanced SQL with window functions and CTEs, semi-structured analysis on VARIANT (FLATTEN, GET_PATH, PARSE_JSON), data modeling, Snowsight worksheets and dashboards, BI tool integration (Tableau, Power BI, Sigma), and Cortex Analyst for natural-language to SQL.

Assessment

Multiple-choice and multiple-select items on the live exam

Time Limit

115 minutes

Passing Score

750/1000 (scaled)

Exam Fee

$375 USD (Snowflake / Pearson VUE)

SnowPro Advanced Data Analyst Exam Content Outline

17%

Data Ingestion and Data Preparation

COPY INTO from S3/Azure/GCS, file formats (CSV, JSON, Avro, Parquet, ORC, XML), Snowpipe and Snowpipe Streaming, external tables, managed Iceberg tables, and data quality validation prior to analysis.

22%

Data Transformation and Data Modeling

Star and snowflake schemas, dimensional modeling, MERGE for upsert, dynamic tables for declarative transformations, materialized views, and modeling semi-structured data with VARIANT, OBJECT, and ARRAY.

32%

Data Analysis

CTEs (WITH, RECURSIVE), window functions (ROW_NUMBER, RANK, LAG, LEAD, NTILE, ROWS BETWEEN), advanced JOINs including LATERAL FLATTEN, set operations, semi-structured queries with PARSE_JSON, GET_PATH, FLATTEN, ARRAY_AGG, and Cortex Analyst for natural language to SQL.

29%

Data Presentation and Data Visualization

Snowsight worksheets, dashboards, charts, alerts, Streamlit in Snowflake apps, BI tool integration (Tableau, Power BI, Sigma, ThoughtSpot, Looker, Qlik, Mode), result caching for dashboards, and Data Metric Functions (DMFs) for quality metrics.

How to Pass the SnowPro Advanced Data Analyst Exam

What You Need to Know

Passing score: 750/1000 (scaled)
Assessment: Multiple-choice and multiple-select items on the live exam
Time limit: 115 minutes
Exam fee: $375 USD

Keys to Passing

Complete 500+ practice questions
Score 80%+ consistently before scheduling
Focus on highest-weighted sections
Use our AI tutor for tough concepts

SnowPro Advanced Data Analyst Study Tips from Top Performers

1Study to the official 17/22/32/29 weighting and treat Data Analysis and Data Presentation as your priority focus.

2Master window functions (ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, FIRST_VALUE, NTILE) including PARTITION BY, ORDER BY, and ROWS BETWEEN frames.

3Practice semi-structured queries on VARIANT: PARSE_JSON, GET_PATH, FLATTEN with LATERAL JOIN, OBJECT_KEYS, ARRAY_AGG, ARRAY_FLATTEN.

4Know when to use materialized views, dynamic tables, or query result caching for dashboard performance.

5Compare clustering keys, search optimization service, and JOIN reordering when reading a Snowflake Query Profile.

6Practice connecting at least one BI tool (Tableau or Power BI) and explaining live vs extract / DirectQuery vs Import tradeoffs.

7Use Cortex Analyst on a sample semantic model so you can recognize how it complements (not replaces) hand-written SQL.

8Run timed sets at 65 questions in 115 minutes to build the same pacing the live exam demands.

9Confirm SnowPro Core (COF-C02) is active before scheduling and remember the 2-year validity and 7-day retake rule.

Frequently Asked Questions

What is the format of the SnowPro Advanced Data Analyst exam?

DAA-C01 is a 65-question exam delivered in 115 minutes through Pearson VUE, available online proctored or onsite. The exam includes multiple-choice and multiple-select scenario items. Snowflake may include unscored experimental items that do not affect your final score, and results are reported on a 0-1000 scaled scoring system.

What score do I need to pass DAA-C01?

You need a scaled score of 750 out of 1000 to pass. Because Snowflake uses scaled scoring, the percentage of items you answer correctly is not the same as 75 percent. The best strategy is balanced strength across all four domains, especially Data Analysis and Data Presentation which together account for 61 percent of the exam.

What are the official DAA-C01 domain weights?

The blueprint covers Data Ingestion and Data Preparation (17%), Data Transformation and Data Modeling (22%), Data Analysis (32%), and Data Presentation and Data Visualization (29%). Data Analysis is the largest domain, and analysts should be especially strong in window functions, CTEs, and semi-structured handling on VARIANT.

Do I need a prerequisite to take DAA-C01?

Yes. Snowflake requires an active SnowPro Core certification (COF-C02) as a prerequisite for all SnowPro Advanced exams, including Data Analyst. Snowflake also recommends 1+ year of hands-on Snowflake analytics experience plus advanced SQL fluency, including window functions and semi-structured queries.

How does DAA-C01 align with current 2026 Snowflake features?

Expect scenario items that reference current Snowflake AI Data Cloud features including Cortex Analyst (natural language to SQL), Snowsight dashboards and AI assistant features, dynamic tables, managed and externally-managed Iceberg tables, Snowpipe Streaming, Streamlit in Snowflake, and Data Metric Functions (DMFs) for column-level quality validation.

How much does the exam cost and what is the retake policy?

Advanced exams cost $375 USD per attempt, with discounted pricing of $300 USD for candidates testing in India. After a failed attempt, you must wait 7 calendar days before retaking. Snowflake allows up to 4 retakes of the same exam within a 12-month period, and each retake requires full payment.

How should I study for SnowPro Advanced Data Analyst?

Anchor your prep on the official 17/22/32/29 blueprint and spend most of your time on Data Analysis and Data Presentation. Practice writing window functions, CTEs, recursive queries, FLATTEN with LATERAL JOIN, and PARSE_JSON traversal. Build a Snowsight dashboard end to end, connect at least one BI tool, and use Cortex Analyst on a sample model. Most candidates need 60-100 hours of study.