One very common and, of course, the most famous term you can come across if you've spent time analyzing data. That is data enhancement vs data enrichment. Often these terms are used interchangeably but let me tell you there is a slight difference. You can make a huge impact on your data practices when you understand the differences.
Let this post break down the nuances between data enrichment and enhancement for you. So that, you can rationally use both the technique to manipulate your data and get the maximum benefits from it.
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Data Enhancement Basics
For data professionals, data enhancement is simply a process of refining the existing database. It's about correcting and updating all the data points. This method is exceptionally relevant for finding missing information, updating contact details, and omitting inaccuracies. Overall, it makes your database complete and deployable.
Why Enhancement Matters
While your customer records only include your prospects' names and email addresses, data enhancement could add their mailing addresses, phone numbers, and other important details. It completes the datasets and helps with better targeting. Recently, a study on market analytics indicated that companies that use data-driven measures in B2B operations have seen an increase in EBITDA in the range of 15% to 25%. So, enhanced data matters a lot. It matters more even because;
Now, it's time to discuss the other side of the coin in our data enhancement vs data enrichment discussion. And, it is about data enrichment. Well, I've already covered a detailed article on the "power of data enrichment to fuel your business success". You can refer to it for a detailed understanding of the concept. Anyway, in the next section, I'm here directly pointing out a few factors of data enrichment in short.
How Advanced Data Enrichment Matters
First of all, data enrichment is slightly different from data enhancement. Here, it involves adding data from external sources to append more in-depth metrics to the existing database. With advanced data enrichment, the process goes beyond the bar and adds rich and valuable information to the database that you already have.
Let's take an example to understand this.
Suppose you have a bland database where you have prospect names, their numbers, and their social media handles. So, you can raise it one step further by adding your prospect's social media activity using their IDs and getting specific details of their product purchasing capacities. Of course, you can get all these details from any third-party sources; but what I mean here is you can go beyond the traditional means of data.
Now, take a look at how data enrichment matters for your analysis here;
Check out -> How commodities data enrichment boosts product sales
Data Enhancement vs Data Enrichment – Explained
Hope you understand so far that data enhancement and data enrichment are two different words and indicate different meanings. While data enhancement indicates adding some additional data to your database; whereas enrichment means going deeper with your data. It fuses deep data insights into your system. Anyway, here a detailed analysis is made between data enrichment and enhancement for a quick scan.
| Aspect | Data Enhancement | Data Enrichment |
|---|---|---|
| Data Source | Internal (Polishing the existing data) | External (Adding new data insights) |
| Purpose | To provide current data a complete look, make it more consistent and accurate. | Introduce new data from external sources to add fresh information and new insights. |
| Scope | Refine what’s already inside the database. Polish it and make it usable. | Expand the limits of your existing data by adding new insights from external sources. |
| Focal Area | Sharply increase the quality of your existing data | Add deep and quantified insights into your existing data |
| Process |
|
|
| Outcomes | Make database reliable because of precise datasets. | Present a comprehensive and insightful picture of your data. |
Make Your Data Processing Simple
Whether it's data enhancement vs data enrichment or any other matters, make sure you choose the right technique to process your data. After all, you want to use the best of your data. Well, have you ever thought about outsourcing your data enrichment needs? Well, let me tell you outsourcing is amazing. Many companies like AskDataEntry provide data enrichment outsourcing services to ease your data processing tasks. Simply delegate your task and enjoy the benefits of enriched or enhanced data.
