In today’s digital era humans produce close to 2.5 quintillion bytes of data every day. Dirty data is a concern for businesses whatever their size or industry. Any organisation that handles duplicate, inaccurate and outdated information will have to deal with consequences such as:
- Ineffective marketing efforts
Most businesses these days use targeted promotional campaigns. But what happens when the customer information in your records is dirty? Then it must be corrected. This drains time, revenue and effort.
- Poor decisions
Data drives decision making for businesses. But if decisions are made based on bad data, then this leads to costly errors.
- Bad customer experience
A business needs to maintain solid communication with its current and prospective customers to develop a loyal customer base and sustained buyers. But when data used to contact customers isn’t scrubbed, the quality of interaction takes a hit. It can be frustrating for a customer when they experience something they do not expect/deserve. This can also lead to customer churn.
Therefore, data cleansing is vital for every business. Data cleansing is the process of identifying and rectifying corrupt or flawed data from a data set, table or database. It helps you substitute, alter or delete dirty data.
Elements of Data Cleansing
Data cleansing includes five elements — data standardisation, data validation, data analysis, quality check and data deduplication.
Most businesses use data from multiple sources such as data warehouses, cloud storage and databases. But data from distinct sources may not be in a consistent format, leading to trouble down the line. This is where data standardisation helps. It is the process of converting data into a consistent format.
It is the process of organising data within a database. This involves making data tables and identifying relationships between those tables based on the rules designed to reduce data redundancy and improve data integrity.
Data analysis is the process of analysing data using logical and analytical reasoning to get valuable insights. The derived information helps make sensible decisions.
Businesses need good quality data to make the right decisions. Therefore, quality checks are essential.
Data deduplication refers to the process of eliminating duplicate data by deleting any additional copies of a file. This leaves just a single, clean copy to be stored.
In this process, data gets divided into several blocks. These are then compared with each other and a unique hash code is assigned to each block. If the hash code of one block matches the hash code of another, it is considered a duplicate copy and gets deleted. This ensures that only a unique copy of the data is stored. Deduplication can detect redundant copies of data across data types, directories, servers and locations.
Importance and Benefits of Data Deduplication
Most small and medium businesses have limited storage capacity But the amount of data generated, transferred and stored is steadily growing. The process of data deduplication helps tackle this issue by:
- Reducing the storage space requirement by storing only a single copy of a file
- Reducing the network load.
Deduplication helps your business:
- Recover faster after an incident
- Save on storage costs
- Improve productivity
- Reduce version control issues
- Enhance collaboration
- Meet compliance regulations
Always remember that training and process documentation helps empower your employees to be a part of deduplication efforts.
You do not have to begin your deduplication journey alone. We are here to help. Our expertise and knowledge make integration of the process into your business easy.