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Databricks Data Analyst Exam Questions with Verified Answers
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Databricks Data Analyst Exam Questions with Verified Answers
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Databricks Data Analyst ExamQuestions with Verified Answers
Describe the purpose of Databricks SQL endpoints/warehouses. - Answer--They
provide general compute resources for SQL queries, visualizations, and dashboards.
-SQL endpoints provide a way to separate the compute resources used for SQL
workloads from other workloads in the Databricks workspace.
-Databricks SQL supports three types of SQL endpoints: Serverless, Pro, and
Classic.
Identify Serverless Databricks SQL endpoint/warehouses as a quick-starting option -
Answer--A quick-starting option for running SQL queries and visualizations in
Databricks.
-Designed to be easy to set up and use, and provide a cost-effective way to run
queries and exploratory analysis
-Serverless endpoints are optimized for lower-cost, lower-performance workloads
compared to Classic and Pro
Describe the trade-off between cluster size and cost for Databricks
SQLendpoints/warehouses. - Answer-Larger clusters can handle more concurrent
queries and larger workloads, but also cost more to run
Identify Partner Connect as a tool for implementing simple integrations with a
number of other data products - Answer--provides a simpler alternative to manual
partner connections by provisioning the required Azure Databricks resources on your
behalf, then passing resource details to the partner
-allows you to create trial accounts with select Azure Databricks technology partners
-designed to make it easy to connect your Databricks workspace to partner
solutions, without requiring you to manually configure and manage complex
integrations
Describe how to connect Databricks SQL to ingestion tools like Fivetran - Answer-1.
Click Partner Connect
2. Click Fivetran (or the partner you want)
3. Enter your info, then click Connect to Fivetran/Partner
4. A new tab opens in your browser with the partner website. Complete the log in.
5. Follow the instructions to set up a connector, then set up an destination for the
data
6. In DB, create an endpoint, and a warehouse and table to receive the ingested
data
7. Configure the destination in Fivetran, and Fivetran will then start ingesting your
data
What should you do if you have an existing partner account? - Answer-Follow the
steps to connect to the partner solution manually in the appropriate connection
guide. This is because the connection experience in Partner Connect is optimized for
new partner accounts.
, What is small-file upload? - Answer-A solution for importing small text files like
lookup tables and quick data integrations!
Import from object storage using Databricks SQL - Answer-You can import data from
object storage using Databricks SQL by creating an external table that references
the data in object storage. You need to enter a path to the data in the storage with a
link.
When can you ingest directories of files? - Answer-When the files are the same type
and have the same schema. DB reads all the files and combines them in a single
table
Describe how to connect Databricks SQL to visualization tools like Tableau, Power
BI, and Looker - Answer-1. Navigate to the Clusters tab. Click create clusters or
select an existing one
2. In the Advanced Options section, select the JDBC/ODBC tab
3. Follow the instructions to download the JDBC or ODBC driver for your
visualisation tool. Configure the tool using the driver.
Identify Databricks SQL as a complementary tool for BI partner tool workflows -
Answer-By using Databricks SQL as a complementary tool for BI partner tool
workflows, you can take advantage of the scalability and performance of the
Databricks platform while still using the familiar interface of your BI partner tool.
Describe the medallion architecture - Answer--It's a sequential data organisation and
pipeline system of progressively cleaner data
-consists of three layers: bronze, silver, and gold:
-The bronze layer contains unvalidated data in its raw state
-The silver layer represents a validated, enriched version of the data that can be
trusted for downstream analytics.
-The gold layer contains highly refined and aggregated data that powers analytics,
machine learning, and production applications.
Why is the gold layer as the most common layer for data analysts using Databricks
SQL? - Answer--It contains highly refined and aggregated data that power analytics,
machine learning and production applications
-Data shared with a customer would rarely be stored outside this level.
-Because aggregations, joins, and filtering are handled before data is written to the
gold layer, users should see low latency query performance on data in gold tables
Describe the cautions and benefits of working with streaming data - Answer-
BENEFITS:
-real-time insights
-faster decision-making
-ability to respond quickly to changing conditions
CAUTIONS:
-managing the volume and velocity of data
-ensuring quality and consistency
-requires specialised expertise and skills
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