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 for memory space in storage device. Back-up storage devices can be a thumb drive, hard disk drive, SharePoint drive and so on.
How to Reduce Redundancy in 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 in data
DISTINCT keyword
The Distinct syntax can be used with aggregate functions (COUNT, AVG, MIN, MAX, and SUM)
SQL query to remove duplicate rows
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 in data
- Improves database organization upgrade
- Data consistency 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 amongst authorized users in an organization.
- Enhance 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 and optimize tables and queries for the best performance. Principle Component Analysis tool help in mathematically resolving correlated data redundancy issues.
