adplus-dvertising
frame-decoration

Question

What role does data verification play in preventing data corruption?

a.

Data verification ensures data corruption

b.

Data verification is the primary source of data corruption

c.

Data verification is not related to data quality

d.

Data verification can help ensure data accuracy and prevent data corruption

Answer: (d).Data verification can help ensure data accuracy and prevent data corruption Explanation:Data verification can help ensure data accuracy and prevent data corruption.

Engage with the Community - Add Your Comment

Confused About the Answer? Ask for Details Here.

Know the Explanation? Add it Here.

Q. What role does data verification play in preventing data corruption?

Similar Questions

Discover Related MCQs

Q. In a data warehouse, why is deduplication of names and addresses essential?

Q. What are some inherent problems with entering names and addresses in the multiple field format?

Q. What is a key challenge in recasting name and address data into the multiple field format?

Q. How can costs related to bad decisions based on routine analysis be estimated?

Q. Data cleansing tools primarily serve which two main functions for improving data quality?

Q. What are some features of error discovery functions in data cleansing tools?

Q. What are some features of data correction functions in data cleansing tools?

Q. How can data cleansing tools assist in the reconciliation of problems related to RDBMS referential integrity?

Q. What is the purpose of "Update Security" in the database management system for data quality control?

Q. What does "Conformance to Business Rules" in the database management system involve?

Q. Why do some companies resist data cleansing initiatives?

Q. What is the "clean as you go" approach to data cleansing in the context of a data warehouse?

Q. What is one of the drawbacks of the "clean as you go" approach to data cleansing?

Q. What principle should be applied when determining the extent of data cleansing for a data warehouse?

Q. What fundamental question must be answered when deciding which data to cleanse?

Q. Where in the data flow process can data cleansing be applied?

Q. What is a drawback of cleansing data in the staging area?

Q. Why is cleansing data in the source systems a complex task?

Q. What factors should you consider when deciding whether to use vendor tools, integrate cleansing toolkits with ETL tools, or use in-house programming for data cleansing?

Q. What is the first step in assessing the extent of data pollution before applying data cleansing techniques?