Service Definition
The Data Quality Enhancement and Cleaning service provides advanced solutions to improve data accuracy, enhancing its usability and facilitating thorough analysis. The service aims to organize data by addressing errors and duplicates, applying standardized formatting such as date unification, column structuring, and value adjustments to ensure the highest levels of accuracy and efficiency. This service helps reduce data entry errors by setting predefined column types that minimize human mistakes, removing redundant or irrelevant values to focus on essential data. This process enhances data reliability, making it an effective tool for decision-making and improving the efficiency of data-driven operations.
🔔 If you'd like to learn more, please contact us via:
Email: support@datalexing.com
Phone/Whatsapp: +966 539779380
Requirements
Data Source:
Data must be stored in Excel, CSV, or any format that supports analysis and cleaning.
Submitted files should not be linked to any external devices or databases.
A document outlining the general data structure must be provided for ease of understanding and processing.
All formulas within the file must not reference external files to prevent errors during the cleaning process.
Stakeholder Meeting:
A meeting with the responsible team is required to clarify requirements and the purpose of data cleaning.
Work Constraints:
The submitted file must not exceed 50,000 rows to ensure high-quality and efficient processing.
All formulas within the file must not reference external files.
The service does not include data extraction or the development of advanced reports.
Goal Definition:
The client must specify at least three primary objectives they want to achieve through data quality enhancement, such as:
Reducing errors in data entry
Standardizing date and currency formats
Removing duplicates and improving data integrity
Terms
Delivery Timeframe:
The execution timeline will be determined based on data size and complexity, with an estimated duration provided after the initial data assessment.
Data Cleaning Policy:
The provided data must have meaning and value, containing useful and analyzable information rather than being corrupted or unrelated.
The service does not include data recovery but focuses solely on improving the quality of the existing data.
Goal Definition:
The client must clearly understand their objective for the data and define the goals they aim to achieve to ensure a tailored and precise execution.
Understanding the Service:
The client must acknowledge that the service is limited to data quality enhancement and does not include database development or system creation.
Modification Policy:
Clients may request up to two modifications to the cleaned data within two weeks after final delivery, provided they remain within the original project scope.
Delivery
Data Quality Enhancement:
Cleaned data will be delivered according to the agreed-upon standards.
A report will be provided outlining the changes made, such as the number of removed duplicate values, corrected errors, and applied formatting rules.
User-Friendly Design:
Data will be formatted in a way that makes it accessible to non-technical teams.
A user guide will be provided to help maintain data quality in the future.