Benefits of Understanding Data Cleansing Methods
What are the benefits for a company in understanding how to perform data cleansing? Below, we explain three key effects and benefits.
Improving Operational Efficiency
Understanding data cleansing methods improves operational efficiency. If data cleansing is not performed, you may be unable to find relevant data during searches due to inconsistent formatting.
Data must be corrected to find target information and save time on future searches. Identifying misspellings and inconsistencies in a massive database is time-consuming, and regular operations are often interrupted during this process. These tasks would be unnecessary if data were entered according to established rules.
By performing data cleansing to eliminate inconsistencies and discrepancies, you can find relevant data immediately upon searching, saving the time and labor otherwise spent on manual corrections. Saving this unnecessary effort allows operations to proceed smoothly.
This increases the time available for marketing and other core tasks, or for necessary breaks, thereby advancing operational efficiency. As a result, this leads to improved productivity.
Accelerating Decision-Making
Data cleansing accelerates corporate decision-making. Beyond the ease of finding data, the quality and accuracy of the data also play a significant role.
Using well-maintained, high-quality data enables accurate data analysis. The results of such analysis serve as reliable evidence, which is instrumental in determining corporate strategy and direction.
By making important decisions quickly, you can implement effective strategies ahead of competitors. This increases the likelihood of improving business performance and securing a solid position in the market.
Protecting Trust
Analyzing old or incorrect data will not yield accurate results. Data errors and deficiencies are the root cause of various troubles and problems.
For example, conducting sales activities based on incorrect customer data will not produce results, and presenting inaccurate information will cause you to lose the trust of your customers. You might also accidentally send emails to the wrong recipients due to errors in customer data.
Creating sales forecasts or reports based on inaccurate information will not lead to improved performance. If customer satisfaction and service quality decline, and serious errors accumulate, it could lead to a loss of the company's overall reputation.
Data cleansing is essential to protect the trust and credibility of your company.
Methods of Data Cleansing
Methods for data cleansing include manual execution or the use of specialized tools and services.
Manual Execution
Data cleansing can be performed manually, and no special qualifications are required. You can organize data manually using free tools and functions such as spreadsheets or Excel.
It is also possible to proceed with data processing by utilizing functions, programming languages, or database languages like SQL. Advanced processing is best handled by engineers or programmers.
If no engineers are available, employees familiar with data processing can handle it to a certain extent. However, it is important to ensure that this does not interfere with their primary duties.
Manual execution requires time, labor, and a certain level of skill and knowledge, making it more complex and cumbersome as the volume of data increases. The possibility of errors also increases.
Utilizing Specialized Tools and Services
As IT adoption rapidly advances, the number of companies providing tools and services dedicated to data cleansing has increased. Requesting such external services is also a useful option.
Even if your company lacks the necessary personnel or resources, introducing a tool allows you to perform data cleansing smoothly. Using tools or services enables rapid data integration and conversion, streamlining the process. While there is a cost to implementation, the simplification and automation of data processing allow for more complex, ongoing cleansing tasks.
There are various services and tools available, and it is important to compare and evaluate several options before introducing one that aligns with your company's objectives.
Key Points for Considering Data Cleansing Tools and Services
When introducing specialized tools or services, focus on the following points:
- Volume of data held
- Quality of information obtained
- Cost-effectiveness
Companies providing external services and tools possess their own proprietary databases. The larger the volume of information they hold, the more comprehensive the data verification can be. It is also important to look not only at quantity but also at quality, such as the freshness of the data.
Check the information items that can be obtained. For corporate information, if you can supplement not only basic information such as industry, company name, and address, but also information such as capital, number of employees, and sales, you can complete higher-quality data.
It is also important to understand the scale and volume of your company's database. After clarifying how much budget can be invested and how much profit can be expected from the introduction, consider the appropriate functions and plans.
How to Proceed with Data Cleansing
Data cleansing follows a flow of identifying, importing, formatting, and classifying data. Below, we explain the specific steps.
Identifying Data
First, check the database handled by your company to identify what kind of omissions or duplicates exist. It is necessary to identify the targets for data cleansing after correctly grasping the current situation.
Decide on the data format to be cleansed and extract only the necessary data from multiple databases. Performing cleansing on data that contains unnecessary items is inefficient as it increases unnecessary work.
Importing Data
Once you have collected the necessary data, move on to the import stage. After deciding the scope of the data to be imported, import various file formats such as Excel, Word, log files, CSV, and PDF into a single database. Converting inconsistent file formats into the same format during import makes subsequent processing smoother.
Consolidating into a single database reduces the effort of the work and may also reveal new correlations or relationships between data.
Formatting Data and Executing Data Cleansing
After importing the data, perform data formatting. Data formatting is the most important process in data cleansing.
Based on the standards set by your company, correct inconsistencies in notation or character types and delete unnecessary data. It is recommended to set standards for each purpose of data cleansing.
Examples are shown below.
- Standardize full-width alphanumeric characters to half-width
- Remove hyphens from phone numbers and postal codes
- Standardize multiple entries of the same corporate name
- Update old registered addresses to new addresses
By clarifying standards and rules, you can perform cleansing efficiently.
Classifying Data
After formatting the data, organize and classify it. It is important to create lists by data usage purpose and save the data in appropriate locations.
It is best to manage data in a form that allows for immediate retrieval when necessary. Classified data can be utilized for marketing and sales activities.
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