SNOWFLAKE QUIZ – 11 – NiC IT Academy

SNOWFLAKE QUIZ – 11

By Mr.Chandra

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1) You are working on a Snowflake project where you need to analyze data from different business units within your company. Each unit has its own data warehouse in Snowflake. What Snowflake feature would allow you to share data securely across these business units while maintaining data governance?

Virtual Warehouses

Secure Data Sharing

Materialized Views

2) A client is using Snowflake to manage multiple data marts. They want to ensure that their most resource-intensive queries do not degrade performance for other users running queries on the same data. How can you architect the system to achieve this goal?

Create separate Virtual Warehouses for the data marts and assign them different compute clusters

Enable Query Acceleration and prioritize resource-intensive queries

Increase the warehouse size to handle the heavy queries

3) You are setting up a Snowflake data pipeline for a global company that requires the same data to be accessed and updated from multiple regions. Which Snowflake feature would allow you to replicate data across regions to ensure data consistency and availability?

Materialized Views with automatic refresh

Cross-Region Secure Data Sharing

Snowflake Data Replication

4) A project requires you to create an audit log of all changes made to specific tables in Snowflake over a 90-day period. You need to ensure that no change is missed and that this log is readily accessible for regulatory compliance. What Snowflake features would you use?

Time Travel and Streams to capture and audit changes over time

Data Cloning to take daily snapshots of the tables

Fail-safe and Time Travel combined with a periodic data backup

5) You are working on a Snowflake project where data needs to be loaded from multiple sources and transformed into a standard format for reporting. Some transformations are resource-intensive, and your goal is to minimize the impact on concurrent queries. What would be the best approach?

Load all the data into Snowflake and perform transformations in real time during reporting

Use a multi-cluster warehouse with dedicated clusters for ETL transformations and reporting

Use a larger warehouse size to handle both transformations and reporting simultaneously

6) You are managing a project that requires strict data privacy and access control for sensitive information stored in Snowflake. What combination of features should you use to ensure data is only accessible to authorized users while maintaining efficient data sharing?

Virtual Warehouses and Secure Views

Secure Data Sharing with Role-Based Access Control (RBAC)

Query Caching and Result Caching to restrict access to shared data

7) You are leading a Snowflake project for a multinational retail company that needs to handle massive spikes in query traffic during peak shopping seasons. What is the best strategy to maintain high performance without overprovisioning resources year-round?

Increase the default warehouse size and leave it running at all times

Use result caching to minimize the need for running the same queries during peak times

Set up a multi-cluster warehouse with auto-scaling enabled to dynamically adjust resources

8) Your Snowflake project involves working with highly sensitive financial data. The client wants to ensure that no data is permanently deleted, even if it is accidentally dropped or truncated. What Snowflake feature would you recommend to meet this requirement?

Use Time Travel with a retention period and enable Fail-safe

Set up streams and tasks to capture all data changes in real time

Enable encryption and regularly back up data externally

9) You are tasked with setting up a Snowflake environment that provides analysts with access to raw data for exploratory analysis, while ensuring production datasets are protected from accidental modification. What would be the best approach?

Create separate virtual warehouses for analysts and production teams, and apply row-level security

Use Zero-Copy Cloning to provide analysts with copies of production datasets, while protecting the original

Implement Result Caching so analysts work with cached data instead of the raw datasets

10) You are setting up a Snowflake project that requires complex transformations on large datasets for machine learning purposes. The data needs to be transformed, cleaned, and aggregated regularly. Which approach ensures efficient processing while optimizing compute resources?

Perform the transformations using Snowflake’s Virtual Warehouses and enable auto-suspend

Use Materialized Views to perform all data transformations automatically

Create a dedicated ETL pipeline using Snowflake Streams and Tasks

11) Your team is tasked with migrating a legacy on-premises data warehouse to Snowflake. The data consists of billions of rows stored in tables that contain both structured and semi-structured data. What would be the best approach to migrate the data efficiently while ensuring performance and scalability in Snowflake?

Load all data as-is into Snowflake using COPY INTO and optimize queries afterward

Migrate the structured data into relational tables and store semi-structured data in VARIANT columns

Use an ETL tool to transform the data and load it into Snowflake tables in batch mode

12) A retail company wants to analyze customer transactions in real time. The data is ingested continuously from multiple stores into Snowflake. The challenge is to keep the dashboards updated with the latest data without significant delays. What strategy would you recommend to achieve real-time data analytics in Snowflake?

Use Snowpipe for continuous data loading and Streams to capture changes for dashboard updates

Schedule batch jobs to load data periodically and refresh the dashboard manually

Use Virtual Warehouses with a fixed size to handle both data loading and query execution

13) You are developing a Snowflake-based solution for a financial institution. The company requires the ability to audit every change made to critical tables over the past year. What combination of Snowflake features would allow you to meet this auditing requirement efficiently?

Use Fail-safe and Time Travel to recover historical versions of the data

Use Streams to track changes and Time Travel for point-in-time recovery

Enable Materialized Views on the tables to automatically store changes

14) A media company is using Snowflake to store and analyze large volumes of semi-structured data from IoT devices and log files. The data is constantly growing, and they need to optimize query performance as the data size increases. Which strategy would improve performance for querying this semi-structured data?

Use Snowflake’s VARIANT data type and apply clustering keys on frequently queried fields

Create multiple databases to split the data and reduce query complexity

Manually partition the data based on file size and load it into different tables

15) Your company has a Snowflake account, and different departments (e.g., Marketing, Sales, HR) need to access specific datasets for analysis. However, due to data privacy regulations, certain datasets must remain restricted. What Snowflake feature allows you to manage access efficiently without duplicating data?

Use Secure Data Sharing to create copies of the restricted datasets for each department

Create multiple copies of the data and manually grant access to the relevant departments

Implement Row Access Policies to restrict access based on department roles

16) You are leading a project that involves creating complex, resource-intensive machine learning models in Snowflake. The data is stored in large tables that require frequent joins and aggregations. What approach would you use to minimize query cost while ensuring that the machine learning models have access to the most current data?

Use Materialized Views to pre-aggregate the data and refresh them after every update

Use Virtual Warehouses with Auto-suspend to control compute costs

Use Result Caching to avoid recalculating the same aggregations for each query

17) A healthcare organization needs to comply with strict data privacy regulations (e.g., HIPAA) and ensure that their Snowflake environment is configured to protect sensitive patient information. What is the best combination of features and practices to achieve this?

Enable Time Travel and Fail-safe to retain all historical changes to patient data

Store sensitive data outside of Snowflake and use External Tables for occasional access

Use Secure Views, encryption at rest and in transit, and Role-Based Access Control (RBAC)

18) A financial services company wants to use Snowflake for advanced analytics but needs to ensure that users from different departments cannot view or access each other’s data. Which Snowflake feature provides this level of access control without compromising performance?

Set up separate databases for each department

Implement separate Virtual Warehouses for each department with dedicated compute resources

Use Secure Views and Role-Based Access Control (RBAC) to manage user permissions

19) You are working on a Snowflake project where real-time data processing is crucial. Data from multiple sources is being ingested, and each source has a different latency. How can you ensure that the data processing pipeline remains efficient and scalable without overwhelming Snowflake?

Implement Streams and Tasks to handle data transformations in real-time as the data arrives

Batch the data periodically to avoid real-time processing overheads

Set up multiple Virtual Warehouses to handle the different data sources separately

20) 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?

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

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

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

SNOWFLAKE QUIZ – 11

By Mr.Chandra

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