Data Scrubbing – A Way to Enhance Data Reliability

By |2022-04-19T10:55:22+00:00July 9th, 2020|

One of the most vital assets of a business is its data, which makes good data management the key to running a successful enterprise empire. As organizations grow, their data volume increases over time, making it challenging to identify inaccuracies or errors they may contain manually.

Erroneous data can cost large sums of money. Therefore, businesses need to ensure that their enterprise data is clean, good-quality, error-free, and readily available for reporting and analysis to be cost-and-time effective. This is where data scrubbing comes into play.

Let’s start by understanding data scrubbing and why it is essential.

What is Data Scrubbing?

Data scrubbing refers to cleaning raw data and translating it into an accurate, clean, and error-free form. Your data may be erroneous for various reasons, such as improper formatting, human errors at the time of data entry, and missing data.

Data scrubbing improves data quality by removing duplicate, incorrect, incomplete, or poorly formatted data.

Importance of Data Scrubbing

Effective data cleansing or data scrubbing is essential as it can help businesses direct their resources towards value-adding activities while highlighting opportunities for cost-cutting. Most organizations work with large amounts of data.

With proper management, these inputs enable smooth functioning of daily operations and more accurate decision-making over the long term.Consider the example of a Logistics function at an eCommerce company.

Accessible customer data provide this department with crucial insights, such as which regions create the most orders, what products are currently popular, and the average order size of customers. Armed with this information, the department can arrange their warehouse and delivery processes to ensure quicker and more cost-effective order fulfillment, customer information management, and more accurate market and sales trend analysis.
This information must be analyzed so that the business can make sound decisions to set up successful strategies.

By comparison, erroneous or flawed data would make the analysis incorrect, which can lead to:

  • Time-intensive processes
  • Additional costs
  • Additional labor is required to correct the errors
  • Lower efficiency
  • Poor productivity
  • Poor decision-making

In the long run, persistent data quality issues can lead to your business losing customers due to mounting inefficiency and constant miscommunications. Therefore, it is essential to have a data quality strategy in place. Having insufficient data can make a dent in any organization’s bottom line. The solution is working with clean, accurate data.

The data gathered by an organization comes from various external and internal sources. To get maximum and valid use of data, it must be cleaned and compiled before going through other processes.

Data Scrubbing for Effective Data Management Processes

Data Scrubbing plays a vital role in a wide range of data management processes, such as:

Data Integration

Data Integration is the process of combining data from different sources to be consolidated in a single platform. Ensuring data quality in raw data coming from disparate sources with other structures and formats. A data scrubbing tool cleans the incoming data so that the integrated data set is standardized and formatted before being fed into the destination system.

Data Migration

Data Migration involves the transfer of files from one system to another. It is essential to maintain data quality and consistency during this transfer so that the correct formatting and structure are present and there is no duplication at the destination. A large volume of data is usually involved in this process. Data scrubbing tools help clean your information efficiently, ensuring better data quality throughout the enterprise.

Data Transformation

All data must be transformed before it is loaded onto the destination of your choice to meet the system’s criteria of the format, structure, etc. Data Transformation involves applying specific rules, filters, and data cleaning before being analyzed further. A data scrubbing tool helps cleanse the data using built-in transformations, enabling you to meet the desired operational or technical requirements ahead.

Data Scrubbing in ETL Processes

Data scrubbing helps prepare data for reporting and analyses during the ETL (extraction, transformation, and loading) process. Data preparation ensures that only high-quality data is used for decision-making and analysis. For example, a retail company receives data from multiple sources, such as a CRM or an ERP system, containing erroneous information or duplicate data. A good data scrubbing or data cleansing tool would find out the inconsistencies in data and rectify them. The scrubbed data will then be converted into the standard format and loaded into a target database or data warehouse.

Benefits of Data Scrubbing Tools

Data scrubbing tools can help you skip the tedious process of going through all the data manually by cleansing it through built-in transformations. Cleansing data manually involves going through the entries individually, row-by-row, and inspecting them for any invalidities, missing values, etc.

For example, consider the lead list delivered from your marketing team. Now, imagine going through each contact’s name to verify the complete addresses, phone numbers, and email IDs provided. Think of how much time this process takes and the operational issues that could be created if just a few erroneous entries are left uncorrected. On the other hand, data scrubbing tools can help you eliminate errors via automated processes to systematically inspect the data, using different rules and algorithms to identify any flaws and correct them. Hence, making the analysis and business intelligence more straightforward and more effective.

Data scrubbing tools make it easier to clean data without concerns about mistakes or inaccuracy. Scrubbed data improves your enterprise data quality, making it readily available for accurate and valuable data analysis. Thus, making data scrubbing tools a worthy investment for businesses.

How To Simplify the Data Scrubbing Process

Astera Centerprise offers business users an easy solution for data cleaning and data integration, featuring built-in connectors that can retrieve information from disparate data sources. Various transformations and automated data validation processes help users perform a range of data-related tasks, including data scrubbing, data cleansing, maintaining data quality, and delivering standardized datasets to their chosen destination.

Centerprise contains features, such as Data Cleanse Transformation, that can be used for data scrubbing and attaining a clean data set for further use.

Let’s look at how to scrub data using the data cleansing transformation in Centerprise.

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Figure 1- Data set containing white spaces and formatting issues

The dataset shown in figure 1 contains information regarding different customers, and as you can see, there are some white spaces between the postal codes, and it is not formatted correctly. Thus, we will be using the Data Cleanse transformation on this data set.

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Figure 2 – Features of Data Cleanse Transformation

Figure 2 shows the various cleansing options present in this transformation. You can remove white spaces, letters, digits, punctuation, or specify any other characters you want to remove. Secondly, you can also replace null characters or find and replace any other characters by applying numerous options given in the fields with one click. You can also use custom expressions to clean your data.

Figure 3 shows the data preview after applying the Data Cleanse transformation.

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Figure 3- Cleansed dataset

As you can see, all the white spaces have been removed, and the data is now correctly formatted. Furthermore, it can be transferred to any destination of your choice.

Other transformations like Data Profiling and Data Quality Rules enable users to profile data sets to get a statistical breakdown and set quality standards to identify records that contain errors or warnings.

Conclusion

The easy-to-use interface and drag-and-drop transformations in Astera Centerprise simplify information scrubbing. It allows business users and data analysts to clean high-volume datasets in just a few minutes without writing code. Data pipelines can be set up for data scrubbing using workflow automation and job scheduling features to execute data scrubbing jobs without any manual intervention. Scrubbed and cleansed data can help you save substantial time and resources when transforming data, preventing your business from falling into the negative traps of insufficient data and poor data management.