Data cleansing is the process of detecting and correcting errors and inconsistencies from a data set in order to improve its quality. The aim should not be to clean the data, but also bring about that uniformity to various data sets that are merged from different sources. Also, utmost care should be taken that after cleansing, the data set is consistent with similar data sets used by the company.
How data cleansing is important for your business
8 steps of data cleansing process for better data quality
- Import data: Unclean data from various systems is imported. One can import the data from Excel, CSV, or Tab-Separated Text file format.
- Merge data sets: Data from multiple differently formatted sources (eg excel, csv, sql, sap, salesforce, etc) should be converted and merged into a common database.
- Rebuild missing data: Recreating missing information as and when possible, such as Postcodes, states, country, phone area codes, gender, web address from email addresses, etc.
- Standardize data: Combine the data, separated, or modified to ensure that the same type of data exists in each column. This step ensures that your contact’s first name, last name, email address, mobile phone number, etc. are all in their respective columns.
- Normalize data: Similar data e.g. mister, Mr., mr are all converted to Mr. Or street, st., strt. are all converted to St.). Convert telephone numbers to their standard Telstra format, or otherwise as required. Email and web addresses formats should also be checked, where provided, and reformatted as necessary.
- De-duplicate data: Identify potential duplicates. Seek high accuracy matches with a tolerance for misspelling, missing values, or different address orders. For mission-critical data, these results should be manually reviewed and then update the database accordingly.
- Verification to enrich data: Validate the data against internal and external data sources to append value-adding info. I.e., business contacts can be validated against yellow pages to verify their current phone number and addresses. The same goes for various other fields including credit ratings, geo-codes, key contacts, employee size, profit, revenue, time zones, etc., that can be fetched for each company.
- Export data: The final step is to export that cleansed data in formats such as excel, csv, SQL database, XML, tiff, PDF, or as required.
Who is the best company which provide data cleansing services?
Hi-Tech BPO Services offers complete data cleansing services to meet any data quality challenge for any type of data domains with a single, well-integrated package. The package, comprising of people and procedures has proved its usability time and again to cleanse, standardize and enhance raw client data, ensuring that the data is returned in its most useful, consistent and structured format.
