PRODUCT AND SERVICES DATA CLEANSING
Duplicates
Duplicates refer to two or more identical or very similar entries within a dataset. They can occur in various contexts and for various reasons, but they essentially represent redundant information.
The consequences of duplicate data include:
- Unreliable KPIs
- Increased costs
- Reduction in data integrity
- Operational inefficiencies
Our system searches for duplicate names, descriptions, and numbers on a column and row level.
The user is then given the option to edit, delete, or ignore the duplicates.
![de-duplication cleansing AICA Product Data Cleansing, De-duplication. Our system identifies and manages duplicate entries within datasets, preventing unreliable KPIs, increased costs, reduction in data integrity, and operational inefficiencies. The screenshot showcases the user interface, allowing editing, deletion, or ignoring of duplicates on a column and row level. Product Data](https://aicadata.com/wp-content/uploads/2024/02/duplicates-image-1-1.png)
![language image cleansing](https://aicadata.com/wp-content/uploads/2024/01/language-image-cleansing.png)
Language
- Miscommunication
- Operational inefficiencies
- Integration Issues
- Decreased trust and credibility
Missing Data
Missing Data or “Data Profiling” identifies blank values, field data types, recurring patterns, and other descriptive statistics for an instant 360-degree view of your data. As an example, a data profile can be useful in identifying opportunities for data cleansing and assessing how well your data is being maintained based on various quality dimensions.
The user can drill down and see which product item records are affected, as well as sort, filter, and conceal information about products.
![missing-image-cleansing (1) AICA Product Data Cleansing, Missing Data. Our system employs Data Profiling to identify blank values, field data types, recurring patterns, and other statistics, offering a 360-degree view of your data. The screenshot illustrates the user interface allowing users to drill down, identify affected product records, and perform sorting, filtering, and concealing of information for effective data management.](https://aicadata.com/wp-content/uploads/2024/02/missing-image-cleansing-1.png)
![anomaly image cleansing](https://aicadata.com/wp-content/uploads/2024/01/anomaly-image-cleansing.png)
Anomaly Detection
- Inefficient resource allocation
- Compromised data analysis
- False alarms
- Errors in decision-making
- Reduced predictive accuracy
Want to learn more about our services? Have a look at our enrichment, creation, and comparison sections.