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Databricks Lakehouse Fundamentals Test-solved
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Databricks Lakehouse Fundamentals Test-solved
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Databricks Lakehouse Fundamentals Test-solvedWhat does the Databricks Lakehouse Platform provide to data teams? - Answer- One centralized user interface so that data practitioners work in the same environment
Where does Delta Lake fit into the Databricks Lakehouse Platform? - Answer- It runs under the hood of the Databricks Lakehouse Platform to power queries run
It works in an organization's data warehouse to help migrate data into a data lake
It sits on top of an organization's open data lake and provides structure to the many types of data stored within that data lake
It works in concert with existing tools to bring auditing and sharing capabilities to data shared across organizations
What is true about an organization's data when they use Databricks? - Answer- Data that is stored while it's being processed by Databricks is always encrypted
Which statement is true about queries run from Databricks SQL? - Answer- They automatically connect to business intelligence tools without the need for additional configuration
What describes how the Databricks Lakehouse Platform functions within an organization, at a high level? - Answer- Streaming data lands in multiple data warehouses. It is filtered through Delta Lake, which determines which data warehouse the data should be kept in. That data is then used by data practitioners for their data use
cases.
Structured, semi-structured, and unstructured data are captured in Delta Lake. The data
is then passed to a data lake, where it is given structure and munged for quality. That data is then used by data practitioners for their data use cases.
A variety of data types land in an organization's open data lake. Delta Lake augments that data lake by providing structure and governance to that data. That data is then used by data practitioners for their data use cases.
Real-time data is captured in Delta Lake and ultimately lands in an organization's data warehouse. That data is then used by data practitioners for their data use cases.
The Lakehouse was created by combining the most useful elements of which data management strategies? - Answer- Data lakes and data warehouses
One of the key features delivered by the Databricks Lakehouse platform is that data storage is decoupled from compute. What is a direct benefit of decoupling storage from compute? - Answer- The cost of storage and compute are managed separately and can
be scaled to accommodate more concurrent users or larger datasets independently Delta Lake improves data performance through indexing. What does this refer to? - Answer- Ensuring that data can only be accessed by users who should have access
Ordering table data to maximize query efficiency
Structuring queries to act as if they are performed in a single operation
Enforcing data constraints to satisfy business requirements
What is the access point to the Databricks Lakehouse Platform for machine learning practitioners? - Answer- Databricks Data Science and Engineering Workspace
Databricks Delta Lake
Databricks Machine Learning
Databricks SQL
What are the primary services that comprise the Databricks Lakehouse Platform? - Answer- Unity Catalog, Databricks Notebooks, Databricks Repos
Databricks SQL, Apache Spark, Delta Lake
Databricks SQL, Databricks Machine Learning, Databricks Data Science and Data Engineering Workspace
Delta Lake, Apache Spark, Databricks Security & Governance
Where does Databricks Machine Learning fit into the Databricks Lakehouse Platform? - Answer- It is one of the core services of the Lakehouse Platform, tailored towards data practitioners who need to query data and publish visual insights
It is one of the core services of the Lakehouse Platform, tailored towards data practitioners who need to manage users and workspace governance
It is one of the core services of the Lakehouse Platform, tailored towards data practitioners building data pipelines to make data available to everyone in an organization
It is one of the core services of the Lakehouse Platform, tailored towards data practitioners building and managing machine learning models
Which scenario would be best tackled using Databricks Machine Learning? - Answer- Creating a dashboard that will alert business managers of important changes in daily sales revenue
Setting up access controls to limit data visibility to a particular group within an organization
Tracking and comparing the results of machine learning experiments.
Replacing data silos with a single home for structured, semi-structured, and unstructured data
The Databricks Lakehouse Platform is built on top of some of the world's most successful open-source data projects. Which open source projects were originally created by Databricks and come as managed versions in the Databricks Lakehouse Platform? - Answer- Apache Spark, Redash, MLflow, Koalas
One of the key features delivered by the Databricks Lakehouse platform is ACID transactions. What describes ACID transactions? - Answer- They ensure that data
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