Data is undoubtedly the most important aspect for any business. A business can thrive because of accurate and relevant data, but a business can fail because of erroneous data. Its safe to say that the future of any business, relies upon the authenticity and accuracy of the data they collect.

In the business world, data comes in multiple formats and from multiple sources, be it relevant or irrelevant. With an exuberant amount of data coming into the organization, which is good from the aspect that the company can better understand its customer and business trends, but it comes with a cost. Since the data coming in is raw, there is a high likelihood of having errors and issues within the data that can crumble your data analysis.

There are a few common types of data issues that you would want to avoid having within your data at all costs. Firstly, data duplication. Data duplication occurs when the same data comes into your system. It can occur due to human error – someone simply entered the same data multiple times – or multiple copies of the same record were generated during computing. Data duplication can produce skewed results in your analysis and hold your insights at jeopardy. Secondly, Data inaccuracy can be a big issue as well. Since a lot of data is coming in without any quality checks, there is a high chance that some entries might have inaccurate data or some missing fields. While you can correct a few of such inaccuracies manually, but when the coming in, is inn bulk, it gets very cumbersome, and a proper data scrubbing tool becomes crucial moving forward.

Data Scrubbing Tools:

Technical users with prior knowledge and fluency in programming might even find their way out without a data scrubbing tool since they can write long scripts of code for data cleaning and data quality. However, the business users who don’t have programming expertise face a dead end when it comes to data cleaning, and they have no option other than hiring a programmer. Fortunately for them, now there are data scrubbing tools widely available in the market that makes the life of a data analyst easy. A robust Data scrubbing tool can handle data cleaning, amending, or removing for all your data in a matter of minutes rather than manually writing scripts of code in programming languages.

A data scrubbing tool should have some of the following crucial features

1. Code-free: With a code free interface, business users are empowered to carry out their data related challenges themselves and does not have to rely upon someone else’s work. A code free tool makes data cleaning simple and efficient by saving time and resources
2. Extensive data profiling capabilities: The tool should be able to identify any discrepancies in the source data.
3. Data Quality Checks: They should have the functionality for setting up data quality rules based on which, only relevant data can pass through the pipeline further. All the data that doesn’t meet the rules, can be filtered out.
4. Easy Data Mapping: It is important for correct data cleansing, that the data is mapped correctly into the transformations and destinations. This can be ensured with a code-free, drag and drop interface where business users can visually map their data. This enhances the usability of a data scrubbing tool.
5. Connectors: A data scrubbing tool should also have a wide range of built-in connectors through which you can import your data from multiple sources and deploy data quality rules on them.

Conclusion

Data scrubbing tools are an enormous help in the process of data analysis as they speed up the data cleaning process. These tools give you all-in-one solutions so that you can benefit from analysis-ready data and transfer data in any form.