Data Scrubbing – A Way to Enhance Data Reliability

By |2021-01-12T01:37:52+00:00January 12th, 2021|

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

Erroneous data can cost large sums of money. Therefore, it is important for businesses to make sure that their enterprise data is clean, good-quality, error-free, and can be readily available for reporting and analysis, so that the business operations can be cost-and-time effective.

What is Data Scrubbing?

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

This process improves data quality as it would remove the duplicate, incorrect, incomplete, or poorly formatted data.

Importance of Data Scrubbing

Effective data cleansing processes 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 as well as more accurate decision-making over the long-term.

Consider the example of a Logistics function at an eCommerce company. Clean, accessible customer data provide this department with key insights, such as which regions are creating the most orders, what products are currently popular, and average order size for 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, as well as more accurate market and sales trend analysis.
This information must be analyzed so that the business is able to make useful decisions in order to set up successful strategies.

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

• Time-intensive processes
• Additional costs
• Additional labor 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 ongoing miscommunications. Therefore, it is important to have a data quality strategy in place. Having bad data can make a dent on 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. In order to get maximum and valid use of it, the raw data must be cleaned and compiled before it can go through other data 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, so that it can be consolidated in a single platform. Ensuring data quality in raw data coming from disparate sources, with different structures and formatting can be a very time-consuming and difficult process. Data scrubbing tools clean 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 important to maintain data quality and consistency during this transfer, so that the correct formatting and structure is present and there is no duplication at the destination. A large volume of data is usually involved in this process. Data scrubbing tools help perform the task of cleaning your data efficiently, ensuring better data quality throughout the enterprise.

Data Transformation

Data must be transformed before it is loaded onto the destination of your choice so that it meets the system’s criteria of the format, structure, etc. Data Transformation involves applying certain rules, filters, and data cleaning before it can be analyzed further. Data scrubbing tools help cleanse the data using built-in transformations, enabling you to meet the desired requirements for the operational or technical requirements ahead.

Data Scrubbing in ETL Processes

Data scrubbing helps in preparing data during the ETL (extraction, transformation and loading) process for reporting and analyses. Data scrubbing ensures that only high-quality data is being used for decision-making and analysis. For example, a retail company receives data from multiple sources, such as a CRM or an ERP system, which may contain 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 through 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 that complete addresses, phone numbers, and email ids that have been 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. These tools can help you eliminate errors via automated processes to inspect the data systematically, using different rules and algorithms to identify any flaws, and correcting them. Hence, making the process of analysis and business intelligence simpler and more effective.

Data cleansing tools make it easier to clean data without any concerns of mistakes or inaccuracy. They improve the quality of your enterprise data, making it easily available for accurate and useful 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 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 your 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.

The data cleansing feature can be seen with a simple example below.

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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 properly. 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 simply 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 apply 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 properly formatted. Furthermore, it can be transferred to any destination of your choice.

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

The easy-to-use interface and drag-and-drop transformations in Astera Centerprise simplify information scrubbing, enabling business users to clean high-volume datasets in just a few minutes, without writing any code. Automated processes can be set up using workflow automation and job scheduling features that can execute data scrubbing jobs without any manual intervention. This can help you save substantial time and resources, and transform data, preventing your business from falling into the negative traps of bad data and poor data management.

Download a free trial and get to know more about how Astera Centerprise can help you get clean, high-quality data.