Trifacta Reviews & Pricing

Key Features

Trifacta

• Adaptive Data Quality: Discover and validate data quality issues. Build statistical data profiles to identify complex patterns and suggest quality rules like data constraints, formatting patterns and column dependencies. 
• Data Clustering: Identify similar values within data to form clusters. Leverage intelligent algorithms to compare values and ensure standardization across clusters. 
• Data Pipelines: Model data flows while managing relationships across data sets and recipes. Monitor point-in-time and historical data quality trends for proactive alerting. 
• Collaboration and Sharing: Share workflows, recipes and pipelines with the right permissions to streamline data operations. Use collective intelligence of the teams to make robust decisions. 
• Data Munging: Gauge outliers and value distribution in the dataset to inform the analysis process. Separate, blend and un-nest the datasets to visualize and explore. Eliminate inconsistencies such as null and missing values to standardize the data. 

Limitations

•  Slow when preparing data and creating/loading samples. 
•  Lacks statistical modules for analysis and predictive modeling. 
•  Limited number formats and data types. 
•  Lacks intuitive user interface. 

Suite Support