When it comes to managing data for improved business functionality, the words “data enrichment” and “data cleansing” are sometimes used interchangeably.
DATA CLEANSING – The procedure of locating and or deleting inaccurate or corrupt records from a data set is known as data cleansing.
DATA ENRICHMENT – The terminology of data enrichment is defined as the process of improving and refining raw data.
For instance,
You should remodel your old home because you will soon be hosting a party there. It should feel different and look nice. However, it should also be affordable.
What will you do? Re-build the home after it is demolished?
Or do you abandon the party because you fear it will be too expensive?
Or are you going to do it in the same old house, and do you think the visitors will like it?
Nah!!! Instead, you’ll renew the paint, spend money on the interiors, throw out the old things that are useless, and utilize some of the old stuff by polishing them. It is cost-effective, makes your home look unique, and allows you to have a party.
In a similar vein, data cleansing and enrichment assist you in setting up your business data and providing exceptional customer services.
DATA CLEANSING
The first process is data cleansing, to eliminate any invalid data points, the goal is to find any gaps and abnormalities in the raw data and to have a clean – reliable, consistent, and complete database. Data cleansing is also called data cleaning.
Change is constant, especially in business. As per LinkedIn’s ‘The 2022 APAC State of Sales Report’ – Nearly 50% of APAC sellers say their biggest data challenge is incomplete data. Now a day’s data generation and the process are not a big challenge for computer servers. With such an enormous volume of data, another challenge arises that is keeping databases clean and of the highest caliber.
Let’s say, you have got a lot of messages on your phone. For instance, data cleansing helps you to remove unwanted, fake, and weird messages from your list. After keeping your data hygienic, it leads to your next step which is data enrichment.
DATA ENRICHMENT
After data cleansing is done for the provided data. The next step is Data Enrichment. Once you know that your raw data is accurate, it’s time to make use of it. Data enrichment is also called data enriching. Enriched data is nothing more than high-quality data.
First-party data gathered from internal sources (such as subscription forms) is combined with data gathered from other internal sources or third-party external sources as part of the data enrichment process.
Your data gets better at capturing the reality you’re trying to examine and describe with each new layer of information you add.
The data enrichment process improves on the data you already have. The goal is to get further insights from your data to improve your marketing or sales.
The great majority of brands add value to their raw data in order to use it for prospecting and decision-making
DIFFERENCES
The main distinction between data cleansing and data enrichment is that both include removing outdated or incorrect data as well as correcting mistakes. Data enrichment, on the other hand, is the process of adding information from additional reliable sources to data.
| DATA CLEANSING | DATA ENRICHMENT |
| Removes unwanted data | Fills new data to the existing data. |
| Makes your data reliable | Makes your data-rich and standardized |
| Focuses on complete data | Makes data rich & detailed |
| Focuses on quality of data | Makes data consistent and predictable |
DATA CLEANSING vs DATA ENRICHMENT
- Data enrichment is an ongoing process it should be done regularly as data gets outdated whereas data cleansing depends on the company’s requirements.
- Data enrichment helps to improve the accuracy of data, and data cleansing helps companies to make more promising data-driven decisions for business operations
- Updated, trustworthy raw data is the end result of data cleaning. Data that has undergone enrichment is enhanced with new layers of knowledge.
- Data cleansing is the first step and then comes data enrichment.
- Data enrichment is the act of upgrading the data in various ways to make it more valuable, whereas data cleansing is the process of making sure the data is consistent and predictable.
DATA CLEANSING PROCESS
- Remove data which is irrelevant – Look carefully at your data to determine what is important and what you might not need. Remove information or observations that are not pertinent to your needs later on.
- Data duplication – a method that gets rid of duplicate copies of data and minimizes storage space.
- Structural errors – When you measure or transfer data and find odd naming standards, typos, or wrong capitalization, these are often structural errors.
- Fixing missing value – first identifies the missing value then substitute the missing value with the specific value.
- Verify your data - The final step in data cleansing, is data validation it verifies your data’s authenticity and confirms that it is accurate, consistent, and formatted correctly for usage in subsequent steps.
DATA ENRICHMENT PROCESS
- Enhancing Data Quality – It is a constant process to enrich data. As the needs of the consumers change, it must be done frequently. Businesses can create a continuous enrichment process. A significant warning is to make sure the data is correct and full.
- Data matching process – Another step in the data enrichment process is expanding data. It’s crucial to match data with existing duplicates after data cleansing.
- Data Updates and Management – To guarantee constant and ongoing data quality in the future, data should be regulated such that it is frequently cleansed and validated. The monitoring of data is another method for doing this. Setting up controls to ensure that data is compliant with data quality and business needs is a necessary step in monitoring data. Businesses may also acquire access to other databases while updating data in order to look up additional details on their clients or customers, which they can then add to their own database.
In conclusion data enrichment and data cleansing plays a major role in effective decision-making process. Though data enrichment works in many ways, its key objective is to collect data from the customers and add value to it depending on the business, whereas data cleansing keeps the data hygiene. We at VAST Tec, provide data enrichment services and Data cleansing services wherein we clean, standardize, and de-duplicate our client’s data and assist them in gaining a competitive edge in the market.
Are you thinking to get yours Sales Data Enriched?