Data Cleaning Is
|A.||Large collection of data mostly stored in a computer system|
|B.||The removal of noise errors and incorrect input from a database|
|C.||The systematic description of the syntactic structure of a specific database. It describes the structure of the attributes the tables and foreign key relationships.|
|D.||None of these|
The systematic description of the syntactic structure of a specific database. It describes the structure of the attributes the tables and foreign key relationships.
More Related MCQs on Data Mining
What is use of Data cleaning MCQ?
Data cleaning is a technique that is applied to remove the noisy data and correct the inconsistencies in data. Data cleaning involves transformations to correct the wrong data. Data cleaning is performed as a data preprocessing step while preparing the data for a data warehouse.
What is the use of Data cleaning?
Data cleaning is used to removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset. When combining multiple data sources, there are many opportunities for data to be duplicated or mislabeled.
What is data warehouse MCQ?
A process to load the data in the data warehouse and to create the necessary indexes. A process to upgrade the quality of data after it is moved into a data warehouse. A process to upgrade the quality of data before it is moved into a data warehouse.
What is the aim of data mining MCQ?
Data mining is a process of extracting and discovering patterns in large data sets.
What is clustering MCQ?
Clustering itself can be categorized into two types viz. Hard Clustering and Soft Clustering. In hard clustering, one data point can belong to one cluster only. But in soft clustering, the output provided is a probability likelihood of a data point belonging to each of the pre-defined numbers of clusters.