Data Cleansing: Avoid These Common Mistakes

Are you still wondering whether data is crucial for the success of your business or not? Undoubtedly, the answer is a ‘yes’. About 50% of corporate strategies mention data as one of the fundamental components for providing enterprise value. (https://www.gartner.com/smarterwithgartner/why-data-and-analytics-are-key-to-digital-transformation) Data allows organizations to acquire more customers, improve their processes, and enhance profitability. 

 

Therefore, to gather and analyze relevant data, companies Hire Excel expert. However, before you start analyzing the data, removing all errors and getting clean data is vital. That is why you must adopt a data cleansing strategy.

 

In this blog, you will explore common data cleansing mistakes you must avoid. Let’s dive in!

 

#1 Not Checking the Data Sources

Even before you start cleaning the data, it is crucial to find out where it came from and how it was collected. The data can prove to be useful only when data sources are credible, reliable, and up-to-date. Moreover, you must also ensure that you have the license and permission to use the data. Verifying the data sources will enable you to identify the potential issues relating to data quality like inconsistencies, errors, outliers, and missing values.

 

#2 Not Defining the Goals

When you are not clear about your data goals, cleaning the data properly may not be possible. Therefore, you must find out the questions you want to answer with the help of the data. Think about the standards and formats you must follow. Having clarity of the data goals will allow you to focus on the necessary and relevant data only. As a result, it can save you valuable time and prevent you from spending more time analyzing irrelevant and redundant data.

 

#3 Not Checking the Spellings

It is easy to forget to run a spell check. However, it is a very simple step that makes the data a lot easier to understand and analyze. You can leverage a spell checker to easily pinpoint the misspelled word. Based on the data cleansing tool used, you can also determine values that are not used consistently.

 

#4 Not Removing Spaces

The presence of trailing, leading, or multiple space characters can make it difficult for you to understand data and find meaning. Therefore, before you search, sort, or filter your data, it is vital to remove unwanted spaces and characters. 

 

#5 Not Hiring the Experts

When it comes to data cleansing, many companies choose to do it themselves. However, it may not be a smart decision. Data cleansing is not as simple as it seems to be. There are a lot of technicalities involved. So, if you want to remain competitive in the market, partnering with the experts is the best option. The experts can leverage the right processes and tools and help you quickly pinpoint and correct errors. As a result, gaining access to up-to-date and accurate data becomes simple and easy.

 

Conclusion

Data cleansing is vital to improve the decision-making and productivity of your business. Are you looking for certified data cleansing professionals? ProsperSpark can be your right go-to destination. From airtable consultant to ERP migration, they offer everything a business requires. You can even opt for their consulting Excel services. Contact them today!

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