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Snowflake DEA-C01 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Pipelines and Transformation- ETL/ELT design patterns in Snowflake
  • 1. Data orchestration concepts
    • 2. Staging and transformation layers
      - Streams and Tasks
      • 1. Automating pipelines with Tasks
        • 2. Change Data Capture (CDC) with Streams
          Topic 2: Semi-Structured and Advanced Data Handling- Semi-structured data processing
          • 1. VARIANT data type usage
            • 2. JSON, Avro, Parquet handling
              - Advanced transformation techniques
              • 1. Flattening nested data
                • 2. Complex transformations in SQL
                  Topic 3: Security, Governance, and Data Sharing- Data governance
                  • 1. Data masking policies
                    • 2. Secure data sharing concepts
                      - Access control
                      • 1. Object-level permissions
                        • 2. Role-based access control (RBAC)
                          Topic 4: Performance Optimization- Query performance tuning
                          • 1. Caching mechanisms
                            • 2. Clustering and micro-partitions
                              - Warehouse optimization
                              • 1. Scaling strategies
                                • 2. Concurrency management
                                  Topic 5: Data Engineering Fundamentals on Snowflake- Snowflake architecture for data engineering
                                  • 1. Virtual warehouses and compute scaling
                                    • 2. Storage and compute separation
                                      - Data ingestion concepts
                                      • 1. Continuous ingestion concepts
                                        • 2. Batch loading strategies
                                          Topic 6: Data Loading and Integration- Bulk data loading
                                          • 1. File format handling
                                            • 2. COPY INTO command usage
                                              - Snowpipe and continuous ingestion
                                              • 1. Automated ingestion workflows
                                                • 2. Event-driven loading

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                                                  Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q243-Q248):

                                                  NEW QUESTION # 243
                                                  A telecommunications company collects network usage data throughout each day at a rate of several thousand data points each second. The company runs an application to process the usage data in real time. The company aggregates and stores the data in an Amazon Aurora DB instance.
                                                  Sudden drops in network usage usually indicate a network outage. The company must be able to identify sudden drops in network usage so the company can take immediate remedial actions.
                                                  Which solution will meet this requirement with the LEAST latency?

                                                  Answer: D


                                                  NEW QUESTION # 244
                                                  A company has an application that uses a microservice architecture. The company hosts the application on an Amazon Elastic Kubernetes Services (Amazon EKS) cluster.
                                                  The company wants to set up a robust monitoring system for the application. The company needs to analyze the logs from the EKS cluster and the application. The company needs to correlate the cluster's logs with the application's traces to identify points of failure in the whole application request flow.
                                                  Which combination of steps will meet these requirements with the LEAST development effort?
                                                  (Choose two.)

                                                  Answer: D,E

                                                  Explanation:
                                                  FluentBit is a lightweight, efficient tool to collect, process, and forward logs from the EKS cluster.
                                                  It integrates well with AWS services like CloudWatch or OpenSearch for storing and analyzing logs. OpenTelemetry is an open-source standard for collecting distributed traces, making it ideal for monitoring and analyzing application performance in a microservice architecture. Using these tools requires minimal development effort since they are widely adopted and have strong integrations with AWS.
                                                  Amazon OpenSearch (formerly Elasticsearch) is a fully managed service that makes it easy to store, search, and analyze log data, including traces from distributed systems. It is commonly used to correlate logs and traces because it provides robust querying capabilities and visualization features (via Kibana or OpenSearch Dashboards). This solution offers the necessary tools for log-trace correlation with minimal custom development effort.
                                                  While CloudWatch is suitable for log collection, Amazon Kinesis is more suited for real-time data streaming rather than collecting traces for correlation.
                                                  Kinesis also requires more configuration and development effort compared to OpenTelemetry for tracing.
                                                  Similar to Kinesis, Amazon MSK is primarily used for data streaming rather than trace collection.
                                                  It requires additional setup and custom development for correlation compared to the more straightforward integration provided by FluentBit and OpenTelemetry.
                                                  AWS Glue is primarily used for ETL (extract, transform, load) operations in a data lake. It is not designed for real-time log and trace correlation and would require significant development effort compared to the built-in capabilities of OpenSearch.


                                                  NEW QUESTION # 245
                                                  A large table with 200 columns contains two years of historical data. When queried. the table is filtered on a single day Below is the Query Profile:

                                                  Using a size 2XL virtual warehouse, this query look over an hour to complete What will improve the query performance the MOST?

                                                  Answer: C

                                                  Explanation:
                                                  Explanation
                                                  Adding a date column as a cluster key on the table will improve the query performance by reducing the number of micro-partitions that need to be scanned. Since the table is filtered on a single day, clustering by date will make the query more selective and efficient.


                                                  NEW QUESTION # 246
                                                  A Data Engineer needs to ingest invoice data in PDF format into Snowflake so that the data can be queried and used in a forecasting solution.
                                                  ..... recommended way to ingest this data?

                                                  Answer: C

                                                  Explanation:
                                                  Explanation
                                                  The recommended way to ingest invoice data in PDF format into Snowflake is to create a Java User-Defined Function (UDF) that leverages Java-based PDF parser libraries to parse PDF data into structured data. This option allows for more flexibility and control over how the PDF data is extracted and transformed. The other options are not suitable for ingesting PDF data into Snowflake. Option A and B are incorrect because Snowpipe and COPY INTO commands can only ingest files that are in supported file formats, such as CSV, JSON, XML, etc. PDF files are not supported by Snowflake and will cause errors or unexpected results.
                                                  Option C is incorrect because external tables can only query files that are in supported file formats as well.
                                                  PDF files cannot be parsed by external tables and will cause errors or unexpected results.


                                                  NEW QUESTION # 247
                                                  A media company uploads large video files to Amazon S3 for processing. After processing, the company needs to keep the original files for 90 days in case the files require reprocessing. After
                                                  90 days, the company can delete the files to reduce storage costs. The company stores the processed videos in a different S3 bucket. Which S3 Lifecycle configuration will meet these requirements for the original files MOST cost-effectively?

                                                  Answer: D

                                                  Explanation:
                                                  Keeping the files in S3 Standard for 90 days and using an S3 Lifecycle expiration rule is the most cost-effective option among the choices because the objects only need to be retained for 90 days and then deleted. Adding Glacier Flexible Retrieval would introduce archival and restore behavior intended for longer-term storage, and AWS notes that S3 Glacier Flexible Retrieval is a long-term archival class with a 90-day minimum storage duration. S3 Intelligent-Tiering also adds monitoring and automation charges, and Object Lock/versioning add unnecessary cost and controls beyond the stated requirement.
                                                  Reference:
                                                  https://docs.aws.amazon.com/AmazonS3/latest/userguide/glacier-storage-classes.html
                                                  https://docs.aws.amazon.com/AmazonS3/latest/userguide/lifecycle-expire-general- considerations.html
                                                  https://docs.aws.amazon.com/AmazonS3/latest/userguide/intelligent-tiering.html


                                                  NEW QUESTION # 248
                                                  ......

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