(27)
4.8 out of 5
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Identification | Correctly identify inaccurate, incomplete, or duplicated data from a data source. 12 reviewers of SAS Data Quality have provided feedback on this feature. | 88% (Based on 12 reviews) | |
Correction | As reported in 13 SAS Data Quality reviews. Utilize deletion, modification, appending, merging, or other methods to correct bad data. | 74% (Based on 13 reviews) | |
Normalization | Based on 12 SAS Data Quality reviews. Standardize data formatting for uniformity and easier data usage. | 88% (Based on 12 reviews) | |
Preventative Cleaning | As reported in 12 SAS Data Quality reviews. Clean data as it enters the data source to prevent mixing bad data with cleaned data. | 83% (Based on 12 reviews) | |
Data Matching | Based on 13 SAS Data Quality reviews. Finds duplicates using the fuzzy logic technology or an advance search feature. | 87% (Based on 13 reviews) |
Reporting | Provide follow-up information after data cleanings through a visual dashboard or reports. 13 reviewers of SAS Data Quality have provided feedback on this feature. | 82% (Based on 13 reviews) | |
Automation | As reported in 13 SAS Data Quality reviews. Automatically run data identification, correction, and normalization on data sources. | 82% (Based on 13 reviews) | |
Quality Audits | Based on 13 SAS Data Quality reviews. Schedule automated audits to identify data anomalies over time based on set business rules. | 83% (Based on 13 reviews) | |
Dashboard | As reported in 13 SAS Data Quality reviews. Gives a view of the entire data quality management ecosystem. | 77% (Based on 13 reviews) | |
Governance | As reported in 13 SAS Data Quality reviews. Allows user role-based access and actions to authorization for specific tasks. | 74% (Based on 13 reviews) |
AI Text Generation | Allows users to generate text based on a text prompt. | Not enough data | |
AI Text Summarization | Condenses long documents or text into a brief summary. | Not enough data |