We believe organisations thrive on good quality data but sometimes that's just not achievable with the existing tools. This is where we come in - we employ specialised techniques to assess the completeness of your datasets and make recommendations regarding deduplication, cleansing and future validation.
Data quality management and data profiling services are designed to ensure the accuracy, completeness, and consistency of an organisation's data.
Data quality management and data profiling services typically involve the following steps:
Data profiling
This involves the process of analysing data to identify potential data quality issues, such as incomplete or inconsistent data, duplicate data, and missing data. Data profiling helps organisations gain a better understanding of the data they have and identify areas that require attention.
Data cleansing
Once data quality issues have been identified, the next step is to clean the data. This involves standardising data formats, removing duplicates, and filling in missing data to ensure that the data is accurate and consistent.
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Data validation
Once the data has been cleaned, it is important to validate it to ensure that it meets the requirements of the target system. This involves checking the accuracy and completeness of the data, ensuring that it is suitable for use in analysis and decision-making.
Data monitoring
Data quality management is an ongoing process that involves monitoring data to ensure that it remains accurate and consistent over time. This involves setting up data quality metrics, monitoring data quality trends, and taking corrective action when necessary.
Data deduplication
Ensuring records are unique and in line with data governance frameworks.