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What is the process of data cleansing at TradeData.Pro?
The data cleansing process at TradeData.Pro involves several steps to ensure the accuracy and quality of the data we provide.
Step 1: Removal of duplicate or invalid data
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We eliminate duplicated data or any invalid information from our dataset. This includes removing duplicates that may occur during data collection from multiple sources, data scraping, or data received from authorities or data departments. De-duplication is a significant aspect of this process. Additionally, any irrelevant or blank fields are removed during the cleansing process.
Step 2: Refinement of data structural formats
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We refine any structural issues in the data, such as formatting inconsistencies, localizing translations to English, addressing strange naming conventions, or correcting incorrect data headers. This step ensures that the data is well-structured and easily accessible.
Step 3: Validation of the data
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In the final stage of the data cleaning process, we perform basic validation checks to verify the accuracy and integrity of the data.