Why There’s Demand For Data Cleansing and Enrichment Across Industries

With the dawn of the information age came the saying “data is the new oil”, a saying that has become axiomatic with time. Businesses across verticals are vying to gather every piece of enterprise data they can for their growth. This influx of enterprise data is not without its share of flaws though, as it brings with it a plethora of data errors, and in significant quantities too. 

These data issues bring down the quality, and thus, the value of the data, which is why globally, businesses have spent 89.34 Billion in 2022 for data management. That figure is expected to grow in the coming years, requiring you to hire professional data cleansing and enrichment services to maintain/improve data quality, and consequently, market competitiveness. 

This blog details the significance of data cleansing and enrichment for multiple applications across various industry niches. It is intended to aid in your pursuit of outsourcing those processes and tailoring them to improve your data management strategy. 

How The Influence of Data Cleansing and Enrichment Is Increasing Their Demand

1. Artificial Intelligence (AI) & Machine Learning (ML)

AI has been a buzzword of all industries, not just the IT sector, for decades now, and it’s now making a strong mark on the rest of the world. The global AI market was valued at $136.6 Billion in 2022 and is projected to reach $1581.7 Billion in 2030. What got this technology trending is another technological trend: Big Data. 

Training AI and Machine Learning algorithms via data annotation require large quantities of data that are suited for the application the model is being developed to assist with or take over. And that data should be of high quality to enable the clear demarcation of target objects/segments in it. Otherwise, the algorithms will struggle to correctly identify the target and the resultant model will not function to the expected accuracy level. 

Data cleansing will rid the training data of errors that can lead to poor model development. The data enrichment services provided by experts after cleansing ensure that the data is recent and relevant, helping the fledgling model to become familiar with new data inputs that it may not have gotten with old data. 

2. Internet of Things (IoT)

The internet is the invention that has had the biggest influence on the world. It has led to the growth of other inventions while enhancing some such as smart devices. With even mundane objects like curtains being connected to the internet, there is no dearth of data generated and collected by the systems maintaining them. 

Such interconnected devices operate in the form of a hub or hive, meaning if one device gets affected by false data, then the entire hub will falter and perhaps fail altogether. Thus, the data they will consume from the time they are initialized for operation post-installation should be clean. 

Updates should be provided with the latest drivers so that there are no compatibility or synchronization issues between them. The massive amounts of data they generate should also be cleaned to keep only the valuable portions and discard the rest. 

It not only helps with regular functioning but also with performance diagnostics of these devices. Thus, data scrubbing services are a must-have for this maturing industry, along with enrichment to keep incumbent devices compatible with innovations. 

3. Augmented/Virtual Reality

Smart Devices, the internet, and other technological advancements are reshaping our reality in more ways than one. They are, enabling the recreation of reality in the virtual space altogether with Virtual Reality, or at least, overlaying the virtual on the real world with Augmented Reality. 

Multiple industries are lapping up these technological wonders to enhance many operations, with the most notable in the consumer segment being gaming. This market stood at US$ 7.92 Billion in 2021 and is set to be an estimated US$ 53.44 Billion in 2028.

In the case of the industry market, employee training using AR/VR gadgets is picking up steam since it can help train them in real time. Important information can be displayed on top of the object the person is viewing, helping them to better perform their task and learn on the job. 

With such potential, companies are rushing to use these technologies in many ways. Big Data is feeding the necessary data for their development, meaning there are chances of big errors making it through. One wrong data snippet can misinform an employee under training or cause catastrophic failures. Data cleansing and data enrichment services are, therefore, in demand for the development of AR/VR. 

4. FinTech

Money is still as important as ever but technology is making hard cash a thing of the past with digital payments. This has spurred the growth of FinTech, a hybrid between the financial and technological sectors. This has many payment applications for online payment processing for many businesses. Hence, this sector not only has to deal with a lot of data but also the high sensitivity of that data. 

Data issues here don’t just mean bad financial records. It could also mean a loophole a cybercriminal can exploit to their advantage. Sometimes, the data issue may not even be intentional but a technical glitch, especially since these payment services often contain many links in the money-transfer chain. 

Speed and accuracy are two uncompromising pillars of data management in this sector. That is why they tend to outsource data cleansing to secure and capable partners. Having reliable data instills confidence in their customers about the capability of the financial institution to handle their financial and personal data. 

Data enrichment also plays a key role here as that financial and personal data keeps changing with time. Submitting outdated financial records for taxation purposes, or trying to use an expired credit card are some of the problems one could face due to outdated financial data. 

Outsourcing enrichment solves this by regularly updating such critical information. With the Fintech Market touching US$ 226.5 Billion worldwide in 2021, and more growth guaranteed, data cleansing and enrichment will also grow alongside. 

5. Retail

Anyone talking about retail should specify that they are talking about physical stores if that is the case because otherwise, people simply assume that the subject is an eCommerce entity. Such has been the impact of this sector in a short period, and it continues to grow steadily at a staggering 56% CAGR worldwide. What continues to grow with it is the massive amounts of data it generates and consumes. 

The data volume growth only becomes exaggerated with the data of physical stores also being included. And an eCommerce business owner will encounter every type of data error possible simply because it covers all types of data. Product Listing information not being accurate is a common one. 

Then there’s inventory mislabeling. Misplacement is another problem as a certain item won’t be in a designated physical location in the warehouse when the records show otherwise. And so on. The solution is to outsource data cleansing services, along with enrichment, for consistent data issue resolution support, something crucial for such a fast-paced industry. 

6. Social Media Management

Digital Marketing is the way to expand brand visibility and build brand value in the digital age. And social media platforms offer the best means of implementing every kind of marketing strategy any company could have. This is because they are simultaneously data distribution platforms and sources of valuable enterprise data. 

The open nature of most of these platforms allows you to post any content of your liking. While this factor may be a positive for your marketing, it has the opposite effect when you mine the platforms for data. Multiple data issues like bloating, duplication, broken/missing information, etc., are the norm. Some of the customer/competitor data may be outdated as well, like profiles of deceased people being present in an inactive state. 

A combination of deep data cleansing and regular enrichment is needed to bring social media data up to the high quality that enables your company to steam ahead. The processes also provide the data for creating and implementing the marketing strategy using these platforms, further incentivizing their adoption. 

Conclusion

Market forces are constantly pushing companies to tweak their data management strategy. The goal is to consume as much data as possible while maintaining a lean operational profile for maximum efficiency. Data cleansing services, along with enrichment, can shave off the unwanted components of your enterprise data, making your data warehouse a great value proposition. You can use the data for multiple applications regardless of your industry niche, thus bringing in the revenue to reach the quarterly targets with ease.