Free Snowflake DAA-C01 Exam Questions

Core Snowflake Technologies:

• Data Ingestion - Structured data (CSV), semi-structured data (Parquet, Avro, ORC, JSON, XML), unstructured data, synthetic data generation
• Data Discovery - Query tables to assess data elements, statistics, data granularity, required transformations, table joins, set operations (UNION, UNION ALL, INTERSECT, MINUS), ASOF JOINs
• Data Enrichment - Snowflake Marketplace, Secure Data Sharing, Internal Marketplace, Private Listings
• Data Integrity - Primary keys, constraints, parent/child table joins
• Data Processing - Data cleansing, conforming, enriching, pipeline automation, scheduling, logging, monitoring, auditing, data lineage
• Data Loading - Snowsight file loading, external/internal stages, tabular/structured data, semi-structured data, unstructured data, DML operations (INSERT, UPDATE, DELETE), external tables
• Snowflake Functions - Scalar functions, aggregate functions, window functions, table functions, system functions, geospatial functions, AI functions, ML functions (Classification, Top Insights, Anomaly Detection), User-Defined Functions (UDFs)
• Data Transformation - CSV, JSON (query and parse), Parquet, XML preparation, data quality issues, handling duplicates and nulls, data type conversion, Data Metric Functions (DMFs), clones
• Data Modeling - Data aggregation and validation, analytic/window functions, pre-math calculations, casting, data enrichment, Time Travel, cloning, semi-structured data functions, dimensional modeling, Data Vault
• Query Optimization - Query execution plans, query profiling, partition pruning, clustering keys, result/metadata/virtual warehouse caching, search optimization service, query acceleration service
• SQL Extensibility - User-Defined Functions (UDFs), User-Defined Table Functions (UDTFs), stored procedures (including asynchronous), regular/secure/materialized views
• Data Analysis - Descriptive analyses using Snowsight dashboards, exploratory ad-hoc analyses using Notebooks and worksheets, diagnostic analyses (finding causes of anomalies, demographics, relationships, statistics, trends), forecasting and predictive analysis
• Data Presentation - Dashboard creation in Snowsight, report building, chart types (bar charts, scatter plots, heat grids, scorecards), BI tools integration, row access policies, Dynamic Data Masking, dashboard maintenance and sharing, subscriptions and updates

Exam Sections (4 Main Domains with Weightings):

1. Data Ingestion and Data Preparation (17%) - Use collection systems to retrieve data (structured, semi-structured, unstructured, synthetic), perform data discovery to identify needed datasets, enrich data using Snowflake Marketplace, use best practice considerations for data integrity structures, implement data processing solutions, prepare and load data into Snowflake, use Snowflake functions
2. Data Transformation and Data Modeling (23%) - Prepare different data types into consumable format (CSV, JSON, Parquet, XML), clean data (identify quality issues, handle erroneous/ambiguous data, handle duplications and nulls, convert data types, use clones, use Data Metric Functions), work with and query data (aggregate and validate, apply analytic/window functions, perform pre-math calculations, perform casting, enrich data, use Time Travel and cloning, use built-in functions for semi-structured data, use native data types), use data modeling to manipulate data for BI requirements, optimize query performance
3. Data Analysis (32%) - Use SQL extensibility features (UDFs, UDTFs, stored procedures, views), perform descriptive analyses (summarize large datasets using Snowsight dashboards, perform exploratory ad-hoc analyses using Notebooks and worksheets), perform diagnostic analyses (find reasons/causes of anomalies or patterns, collect related data, identify demographics and relationships, analyze statistics and trends), perform forecasting (use statistics and built-in functions, make predictions based on data)
4. Data Presentation and Data Visualization (28%) - Create reports and dashboards to meet business requirements (evaluate and select data, set contexts, create and run SQL queries, apply naming conventions, sort and filter data, understand row access policies and Dynamic Data Masking, compare chart types, understand BI tools connection requirements, create charts and dashboards in Snowsight), maintain reports and dashboards (build automated and repeatable tasks, operationalize data for consumption, manage and share Snowsight dashboards, configure subscriptions and updates), incorporate visualizations for dashboards and reports (present data for business-use analyses, identify patterns and trends, identify correlations among variables, troubleshoot common issues, customize data presentations)

Advanced Skills Tested:

• Preparing and loading data from various sources (structured, semi-structured, unstructured)
• Performing data transformations for data analysis
• Building and troubleshooting advanced SQL queries in Snowflake
• Using Snowflake built-in functions and creating User-Defined Functions (UDFs)
• Performing descriptive and diagnostic data analyses
• Performing predictive data analysis and forecasting
• Preparing and presenting data to meet business requirements
• Creating and maintaining dashboards and reports in Snowsight
• Integrating BI tools with Snowflake
• Optimizing query performance using query profiling, clustering, and caching
• Working with data modeling techniques (dimensional, Data Vault)
• Using SQL extensibility features (UDFs, UDTFs, stored procedures)
• Understanding and applying row access policies and Dynamic Data Masking