Chapter 4 Building a Modern Cloud Data Platform with Databricks

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What makes it challenging to combine appends and reads, and batch and streaming jobs?

The lack of consistency and isolation of data lakes (correct)

The optimization of data warehouses for structured data

The need for flexibility in data management systems

The requirement for real-time monitoring and SQL analytics

What has been a consequence of the limitations of data lakes?

The development of more specialized systems for diverse data applications

The loss of benefits of data warehouses (correct)

The reduction of the need for high-performance data management systems

The materialization of all the promises of data lakes

What is the primary drawback of the data warehouse approach?

High operational cost and scalability

Vendor lock-in and limited data formats (correct)

Inability to handle large amounts of data

Lack of competitiveness and reputation

What type of data are recent advances in AI primarily focused on processing?

Unstructured data Signup and view all the answers

What is a common approach to address the increasing needs of data management?

Using multiple systems, including data lakes, data warehouses, and specialized systems Signup and view all the answers

What is the main advantage of the lakehouse approach?

Cost-effective and scalable Signup and view all the answers

Why is scalability essential in DM solutions?

It contributes to competitiveness, efficiency, reputation, and quality Signup and view all the answers

What is a drawback of using multiple systems for data management?

Additional complexity and delays in data movement Signup and view all the answers

What is the primary benefit of using a single, unified data management system?

Reduced complexity and delays in data movement Signup and view all the answers

What is the primary reason for companies being forced to create multiple data copies?

To make data accessible to other third-party systems Signup and view all the answers

What is the characteristic of data storage in a lakehouse?

Stored in open data formats Signup and view all the answers

Why is the data warehouse approach less cost-efficient?

Due to high operational cost and vendor lock-in Signup and view all the answers

What is a key benefit of using a lakehouse for data analytics and machine learning?

Unifying all data and running analytics and ML in a single place Signup and view all the answers

What is one of the challenges that a lakehouse approach can overcome?

Data becoming stale Signup and view all the answers

What does a lakehouse approach provide in terms of data access?

Complete and firm copy of all data in a centralized location Signup and view all the answers

What is a benefit of using open formats and open standards in a lakehouse approach?

Easy movement of data to a different vendor or technology Signup and view all the answers

What is one of the benefits of unifying data teams in a lakehouse approach?

All data teams can work together on one architecture Signup and view all the answers

What type of data can be managed in a lakehouse approach?

Both structured and unstructured data Signup and view all the answers

What benefits does the lakehouse approach provide in terms of data reliability?

ACID transaction with atomicity, consistency, isolation, and durability guarantees Signup and view all the answers

What is a characteristic of the lakehouse approach to data pipelines?

It enables real-time analytics with streaming data Signup and view all the answers

What is the purpose of Delta Lake in the lakehouse approach?

To bring data reliability to an existing data lake Signup and view all the answers

What is a benefit of the streamlined data pipeline setup in the lakehouse approach?

Reduced compute times and costs with scalable cloud runtime Signup and view all the answers

What is a characteristic of the Spark clusters used in the lakehouse approach?

They are highly optimized Signup and view all the answers

What is the purpose of the lakehouse approach?

To provide modern data engineering best practices for improved productivity, system stability, and data reliability Signup and view all the answers

What type of transactions are necessary to ensure that multiple data pipelines can read and write data reliably on the same table?

ACID transactions Signup and view all the answers

What type of data processing is enabled by Delta Lake across batch and streaming?

Unified streaming and batch data processing Signup and view all the answers

What is the primary goal of creating a central source of truth for business intelligence applications?

To have a single source of truth for BI applications Signup and view all the answers

What is a common challenge faced by companies in business intelligence?

Data is incomplete and stale in a data warehouse Signup and view all the answers

What is the benefit of using Delta Lake for data reliability?

It enables data reliability across batch and streaming Signup and view all the answers

What is the result of having a central source of truth for business intelligence applications?

End-users receive complete, reliable, and up-to-date data Signup and view all the answers