Answer the following statement(s) true (T) or false (F)

Question

1. Organizations employ data warehouses to store junk data.
2. Unstructured data comes from a single source.
3.An SQL database stops abruptly when it encounters an error in the update process.
4. The goal of a NoSQL database is to provide very fast performance even as the amount of data that must be processed continues to grow.
5. Hadoop is designed for processing large volumes of data by dividing the work into a set of independent tasks that are executed in parallel on a large number of servers.

Answer 1

1.FALSE
Data warehouses frequently hold a huge amount of data—often containing five years or more of data. Many organizations employ data warehouses to hold the data they need to make key business decisions.
2.FALSE
Unstructured data exists in huge quantities and comes from many sources such as text documents, electronic sensors and meters, audio files, email, video clips, surveillance video, phone messages, text messages, instant messages, postings on social media, medical records, x-rays and CRT scans, photos, and illustrations.
3.FALSE
SQL databases conform to ACID properties (atomicity, consistency, isolation, and durability) that guarantee database transactions are processed reliably and ensure the integrity of data in a database. If for any reason an error occurs and the transaction is unable to complete all steps in the update process, the database is returned to the state it was in before the transaction began to be processed.
4.TRUE
A NoSQL database is designed to store and retrieve data in a manner that does not rigidly enforce the ACID (atomicity, consistency, isolation, and durability) conditions associated with the relational database model. The goal of a NoSQL database is to provide very fast performance even as the amount of data that must be processed continues to grow.
5.TRUE
Hadoop is an open-source software framework designed for processing large volumes of data by dividing the work into a set of independent tasks that are executed in parallel on a large number of servers. The servers run independently of one another but under the direction of another processor that distributes the work to the various processors and collects their results. This approach creates a very robust computing environment that allows the application to continue running even if individual servers fail.