SNOWFLAKE QUIZ – 12 – NiC IT Academy

SNOWFLAKE QUIZ – 12

By Mr.Chandra

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1) Your company is running a Snowflake instance to manage data pipelines across multiple time zones. Users across the globe are querying data at different times of the day. How would you architect the system to handle variable workloads and ensure optimal performance for all users?

Set up multiple Virtual Warehouses with Auto-suspend to handle workload spikes in different regions

Use a single large Virtual Warehouse and rely on Result Caching to manage query performance

Schedule non-critical queries to run during off-peak hours and prioritize critical ones manually

2) A retail company uses Snowflake to store customer purchase history for personalized marketing. Due to privacy regulations, customers can request to delete their data at any time. How can you ensure the data is permanently deleted while retaining the rest of the dataset?

Use Row-Level Security to restrict access to the deleted customer's data

Implement Data Masking on customer records and mask deleted entries

Use the DELETE command to remove the customer’s data and disable Time Travel for the relevant tables

3) Your company needs to optimize data sharing between two Snowflake accounts for a joint project. The shared data must remain updated and reflect the latest changes from both sides. What Snowflake feature allows you to securely share data between accounts in real time?

Use Secure Data Sharing with automatic synchronization

Create External Tables in both accounts and synchronize them manually

Implement Materialized Views and periodically refresh them across both accounts

4) A project requires the historical tracking of all changes made to a table over the past year. Your goal is to avoid storing unnecessary data but still allow for querying past versions of the table. What Snowflake feature provides this capability efficiently?

Use Fail-safe to store backups of all table versions

Enable Time Travel on the table with a specified retention period

Use Streams to capture and store changes for a year

5) A logistics company needs to analyze delivery routes in real-time to optimize fuel consumption. They have data streaming in from GPS devices every minute. What approach should you take to manage and analyze this real-time data in Snowflake?

Load data in batches every hour and perform historical analysis

Use Snowpipe for continuous data ingestion and Streams to track changes in the data

Implement a third-party tool to process the data before loading it into Snowflake

6) A company wants to ensure that sensitive data stored in Snowflake is encrypted and can only be accessed by authorized users. What combination of Snowflake features would you implement to achieve this?

Use Secure Views and Role-Based Access Control (RBAC) with encryption at rest

Store sensitive data in external files and reference them in Snowflake

Use Data Masking and Time Travel to protect sensitive information

7) Your organization has a significant amount of historical sales data that is rarely accessed but needs to be retained for compliance purposes. What would be the best strategy to store this data efficiently in Snowflake?

Move the data to an external storage solution and delete it from Snowflake

Use Time Travel to retain the data indefinitely in Snowflake

Use Snowflake's Data Retention policies and move older data to a lower-cost storage tier

8) A company has multiple departments that use Snowflake to analyze customer data. Each department requires a different subset of the same dataset, but data privacy regulations prevent them from seeing each other's data. What is the most efficient way to manage this requirement?

Create separate copies of the dataset for each department

Use Row Access Policies to filter data based on user roles

Implement data encryption for each department's dataset

9) You are responsible for managing a Snowflake environment that supports multiple development teams. Each team requires different access levels to the same datasets. How would you best handle this scenario?

Create different databases for each team and replicate the data

Implement Role-Based Access Control (RBAC) to grant different permissions to different roles

Use Secure Views for each team and replicate the data within each view

10) A marketing team wants to analyze user engagement data collected from various channels but needs to perform complex queries that involve joining several large tables. What strategy should you implement to optimize query performance?

Use a single large Virtual Warehouse to execute all queries

Schedule the queries to run during off-peak hours to reduce contention

Use Materialized Views to pre-aggregate and optimize frequently queried data

11) You are tasked with ensuring data quality in a Snowflake pipeline that aggregates sales data from multiple regions. How can you systematically verify the accuracy of the data being loaded?

Implement Data Quality Checks as part of your ETL process and log errors for review

Rely on Snowflake's built-in error handling to catch any loading issues

Run periodic manual checks on the data after loading

12) A company is running a seasonal promotion and expects a significant increase in data volume and user queries during this period. What steps should you take to prepare your Snowflake environment for this expected load?

Increase the size of your Virtual Warehouse and disable auto-suspend

Set up multiple smaller Virtual Warehouses to handle peak loads

Scale up your compute resources dynamically based on current workloads

13) A telecommunications company wants to analyze call detail records stored in Snowflake for customer insights. However, they need to ensure that querying this data does not impact performance for other critical applications. What would be the best approach to achieve this?

Use a dedicated Virtual Warehouse for analyzing call detail records

Load the data into external tables to avoid contention

Share the data with a separate Snowflake account for analysis

14) A financial services organization wants to leverage Snowflake for their reporting needs. They have a requirement for historical data retention for auditing purposes. How can they meet this requirement while minimizing costs?

Store all historical data in a single table with Time Travel enabled

Use a combination of Time Travel and Fail-safe to retain data

Archive old data in cheaper storage solutions while keeping a small subset in Snowflake

15) You are working with a startup that is building a data pipeline in Snowflake to aggregate web traffic data for analytics. The data needs to be refreshed multiple times a day, but the startup is concerned about costs. What approach can you recommend?

Use a single large Virtual Warehouse for all data processing and reporting

Schedule Snowpipe to load data incrementally throughout the day

ad data in batches once a day to minimize costs

16) A healthcare analytics company needs to ensure that their Snowflake environment adheres to strict HIPAA regulations. What steps should you take to ensure compliance while allowing for efficient data analysis?

Use Row Access Policies and Secure Views to restrict access to sensitive data

Enable Time Travel to audit data changes and retain backups

Use encryption for all data at rest and in transit while monitoring access logs

17) What role does micro-partitioning play in Snowflake’s architecture, and how does it affect query performance?

Micro-partitioning enables the automatic scaling of compute resources

Micro-partitions organize data physically to allow for faster scanning during queries based on columnar access patterns

Micro-partitioning limits the number of users accessing the data simultaneously

18) What is the primary advantage of using Snowflake's Multi-cluster Warehouses over single-cluster warehouses?

They offer higher concurrency and better cost management by scaling compute resources based on demand

They automatically clone data across regions for disaster recovery

They compress data more efficiently for storage savings

19) How can Snowflake’s "Task" feature be used in combination with streams to ensure that no data is lost or processed twice in an event-driven architecture?

By using tasks with time-based scheduling to query streams at regular intervals

By using streams in combination with tasks that have a resume policy to ensure exactly-once processing

By creating materialized views that auto-refresh when streams update

20) What happens when you run a MERGE statement in Snowflake on a table with clustering enabled, and how can it impact performance?

The MERGE automatically reclusters the entire table

The MERGE updates only the affected partitions, but a RECLUSTER operation is required to optimize query performance

The MERGE requires the entire table to be loaded into memory, degrading performance

SNOWFLAKE QUIZ – 12

By Mr.Chandra

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