SQL Query to Reduce Redundancy of Data

What is Data

Data is a collection of words, images, sound, letters and observations for analysis, reference and research purpose.

What is Redundancy in Data

Data redundancy is the duplication of data in a table or database. When data is duplicated we consume more memory space in storage devices . Back-up storage devices can be a USB flash drive, hard disk drive, SharePoint drive and so on.

Source: Data Catchup

How to Reduce Redundancy Of Data

In Data analytics, solving redundancy of data is a first step towards analyzing large amounts of data.

Analysts come across unstructured data that need to be put in a structured form. By unstructured we mean collected data that need to be organized. The ability to begin a data mining process is to identify duplicate records in a file, table and database.

In databases we use Normalization to ensure unique records are displayed.

Normalization is a process or set of guidelines used to optimally design a database to reduce redundant data.

The following are the three most common normal forms in the normalization process:

  • The first normal form
  • The second normal form and
  • The third normal form

SQL Syntax to Remove Redundancy Of Data

DISTINCT keyword

The Distinct syntax can be used with aggregate functions (COUNT, AVG, MIN, MAX, and SUM)

SQL query to remove duplicate rows

Source: Data Catchup

The Distinct syntax can be used with aggregate functions (COUNT, AVG, MIN, MAX, and SUM)

Source: Data Catchup

SQL Query to Remove Duplicate rows

Source: Data Catchup


PARTITION divides the query result into partitions.

CTE means Common table expression.

ROW NUMBER numbers the output of a result set.

OVER clause defines a window or user specified set of rows within a query result set.

Benefits of Resolving Redundancy Of Data

  • Improves database organization upgrade
  • Makes Data consistent within the database
  • Creates additional memory space for cloud, computer and auxiliary storage.
  • Encourage much more flexible database design
  • Improves database security
  • Data can be easily shared among authorized users in an organization.
  • Resolving redundancy of data enhances data integration between several tables by strengthening relationship with other data entities for easier update and retrieval of data.

In conclusion, our data need to be cleaned to improve performance and integrity of data. You need to create the right SQL statement, optimize tables and queries for the best performance. Principle Component Analysis tool help in mathematically resolving correlated data redundancy issues.

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