Fundamentals of the Databricks Lakehouse Platform Accreditation - v2

Maintaining and improving data quality is a major goal of modern data engineering. Which of the following contributes directly to high levels of data quality within the Databricks Lakehouse Platform? Select two responses.

schema evolution, Data expectations enforcement

Which of the following architecture benefits is provided directly by the Databricks Lakehouse Platform? Select three responses.

Available on and across multiple clouds. Built on open source and open standards. Unified security and governance approach for all data assets

Which of the following compute resources is available in the Databricks Lakehouse Platform? Select two responses.

Classic clusters. Serverless Databricks SQL warehouses

One of the foundational technologies provided by the Databricks Lakehouse Platform is an open-source, file-based storage format that provides a number of benefits. These benefits include ACID transaction guarantees, scalable data and metadata handling, audit history and time travel, table schema enforcement and schema evolution, support for deletes/updates/merges, and unified streaming and batch data processing. Which of the following technologies is being described in the above statement? Select one response.

Delta Lake

Which of the following describes the motivation for the creation of the data lakehouse? Select one response.

Organizations needed a single, flexible, high-performance system to support data, analytics, and machine learning workloads.

Data organizations need specialized environments designed specifically for machine learning workloads. Which of the following is made available by Databricks as part of Databricks Machine Learning to support machine learning workloads? Select four responses.

Built-in automated machine learning development, Support for distributed model training on big data, Optimized and preconfigured machine learning frameworks, Built-in real-time model serving

Which of the following is a benefit of the Databricks Lakehouse Platform being designed to support all data and artificial intelligence (AI) workloads? Select four responses.

Data workloads can be automatically scaled when needed. Data teams can all utilize secure data from a single source to deliver reliable, consistent results across workloads at scale. Analysts can easily integrate their favorite business intelligence (BI) tools for further analysis. Data analysts, data engineers, and data scientists can easily collaborate within a single platform.

Unity Catalog offers improved Lakehouse data object governance and organization capabilities for data segregation. Which of the following is a consequence of using Unity Catalog to manage, organize and segregate data objects? Select one response.

Databricks SQL

Which of the following Databricks Lakehouse Platform services or capabilities provides a data warehousing experience to its users? Select one response.

Databricks SQL

While the Databricks Lakehouse Platform provides support for many types of data, analytics, and machine learning workloads, some organizations prefer to continue using other preferred vendors for use cases like data ingestion, data transformation, business intelligence, and machine learning.

Databricks can be integrated directly with a large number of Databricks partners.

In the past, a lot of data engineering resources needed to be contributed to the development of tooling and other mechanisms for creating and managing data workloads. In response, Databricks developed and released a declarative ETL framework so data engineers can focus on helping their organizations get value from their data Which of the following technologies is being described above? Select one response.

Delta Live Tables

Data sharing has traditionally been performed by proprietary vendor solutions, SSH File Transfer Protocol (SFTP), or cloud-specific solutions. However, each of these sharing tools and solutions comes with its own set of limitations. As a result, Databricks helped to develop the solution, Delta Sharing. Which of the following describes Delta Sharing as a solution for data sharing? Select one response.

Delta Sharing is a multicloud, open-source solution to securely and efficiently share live data from the lakehouse to any external system.

A data architect is evaluating data warehousing solutions for their organization to use. As a part of this, the architect is considering the Databricks Lakehouse Platform. Which of the following is a benefit of using the Databricks Lakehouse Platform for warehousing? Select four responses.

Engineering capabilities supporting warehouse source data. Local development software to integrate with other capabilities. Built-in governance for single-source-of-truth data. A rich ecosystem of business intelligence (BI) integrations

Which of the following do Databricks SQL users experience when using serverless Databricks SQL warehouses rather than classic Databricks SQL warehouses? Select one response.

Expedited environment startup

Which of the following is a security feature made available in the Databricks Lakehouse Platform by Unity Catalog? Select two responses.

Fine-grained access control on data objects. Single-source-of-truth identity management

Which of the following lists the relational entities in order from largest (most coarse) to smallest (most granular) within their hierarchy? Select one response.

Metastore → Catalog → Schema (Database) → Table

The Databricks Lakehouse Platform architecture consists of a control plane and a data plane. Which of the following resources exists within the Databricks control plane? Select two responses.

Notebooks. Cluster configurations

It can be challenging for a data lakehouse to provide both performance and scalability for all of its query-based workloads to the standards of a data warehouse and a data lake. As a result, Databricks has introduced a technology built atop Apache Spark to further speed up and scale these varied workloads. Which of the following technologies is being described in the above statement? Select one response.

Photon

Which of the following data engineering capabilities simplifies the work of data engineers on the Databricks Lakehouse Platform? Select three responses.

SQL and Python development compatibility. End-to-end data pipeline visibility. Automatic deployment and data operations

Which of the following describes what challenges a data organization would likely face when migrating from a data warehouse to a data lake? Select two responses. .

There are increased security and privacy concerns in a data lake. There are increased data reliability issues in a data lake

Which of the following describes how the Databricks Lakehouse Platform makes data governance simpler? Select one response

Unity Catalog provides a single governance solution across workload types and clouds.