Why Is Data Cleansing Important?
Across all walks of business, the importance of data cleaning is becoming more and more salient. As data grows in size and number, companies and firms must manage it more efficiently and effectively. Dirty data, or data that needs cleaning, may be difficult to understand or pool together. It may also have poor formatting, incoherent structure, or may duplicate many times over.
Dirty data can create a lot of time wastage and expense. Therefore, to be as efficient and as cost-effective as possible, companies can choose to cleanse data. Data cleanup software, such as WinPure, can help break down and tidy up big data lakes.
This can help to automate the collection of future data, as well as to organize existing siloes. The more data held the more likely data cleansing will become necessary over time.
What is the Purpose of Data Cleanup?
The primary purpose of data cleanup is to organize, update and clarify existing records. Over time, big data can clutter, duplicate, and grow challenging to manage. Data such as customer records, which are critical to providing services, need clarity and ease of access. Dirty data adds time, expense, and hassle to this necessity.
Estimates show that, through managing unclean data, a salesperson in the US is likely to waste 27.3% of their overall working time. That is a massive gulf of time better used actively seeking leads and building relationships.
A company will take up data cleaning if they are struggling to keep up with demand. They may also choose to re-organize their data siloes if agents’ workloads become too cluttered as a result. The moment duplicate or poor quality data starts to impact service quality, it is time to consider data cleaning.
Cleaning up dirty data is a process that can apply to and benefit multiple industries. It can also support companies of varying sizes. But what are some of the expected benefits of cleanup across the board?
Data Cleaning Importance and Benefits
The importance of clean data, as mentioned, crosses boundaries. Figures show that the US economy drains at least $3 trillion per year through dirty data management.
However, the importance of clean data is more than an economic concern. Here are a few of the key benefits of cleaning data on a wide scale.
- Cleaning siloes and data lakes can help to remove errors.
- Fewer errors can result in boosts to efficiency and productivity.
- Higher quality data can also ensure higher quality standards of customer care.
- Cleanup can help to set up efficient data maintenance for the future.
- Cleaner data is easier to pinpoint should problems arise in the future.
- Cleaning up can help companies set up more precise business roadmaps and funnels.
- Data cleaning can also help to prevent bottlenecks in service delivery.
Of course, the examples above apply to the broadest spectrum. There are specific cases across industries and businesses where cleanup may be of further benefit.
For example, in healthcare, clearer, more concise records can help speed up patient diagnosis. This data can also ensure more effective medication and treatment precision. As everyone will need a medical record, cleanup can also plan for growing data.
In the banking sector, clean data is equally important. Data cleansing can help to fight against fraud. It can also help to safeguard wealth, as well as to ensure customers receive relevant support.
Across the board, clearer, cleaner data allows for more satisfying customer service. Customers can expect record access to take a matter of minutes, if not seconds. They can also expect relevant products and services based on previous use.
Of course, cleansing is also hugely beneficial to agents and employees, let alone managers. Highly organized data allows for faster processing and fewer additional mistakes. Crucially, cleansing can help to prevent a bad data situation from getting any worse!
Why is Data Cleansing a Major Issue in Business?
Dirty data is a massive problem in modern business. More than a quarter of all business owners suggest that they feel data cleanliness is a problem. However, as discussed, it still costs the economy trillions of dollars each year.
What’s more, data will never stop growing. Even when people pass away, their records remain. These may be patient records in the healthcare industry, banking records in the finance industry, or otherwise. Therefore, without a cleaning solution, data can continue to pile up and cause problems.
Data siloes and lakes continue to be problems mainly as a result of human error. Manual handling of data can lead to 60% of all dirty data cases. Therefore, there is a strong case for data processing to become autonomous.
As demand increases across all business sectors, new data grows. To avoid bottlenecking, businesses must assess their data capabilities and find new ways to collate them. This, crucially, is where cleaning strategies come into play.Find Out More About WinPure Data Quality Tool
Conclusion of Cleansing importance
While outdated data collection standards persist, dirty data will continue to grow. The pressure is building on business owners to organize their data to future-proof their processes for years to come. This is not always going to be an easy task, especially if there are many data sources in play.
Therefore, services such as WinPure offer clear, simple solutions to this common problem. Business owners can safely remove duplicate data and pool records from multiple sources without fear of losing track. WinPure supports leading businesses across various sectors – where there is big data, there is a need for cleansing.
Data silos or data lake models are growing ever-more outdated. Technology, and population booms, outgrow our limited frameworks and methodologies. Therefore, now is undoubtedly time for business owners to consider cleaning up their records.
It is time to take the importance of data cleaning seriously. From thorough data cleaning to linking records, WinPure’s data tools can help solve common business problems and puzzles. Please read more information across our website. For more support, download our free tools. With data growing by the second, now is the time to create a clear, accessible, and efficient future.
Last Updated on 22nd March 2021 by admin