DataWeigher
DataWeigher is a data profiling and exploration tool that allows users to quickly understand data by analyzing statistics, distributions, relationships and more. It generates visual reports to easily identify data quality issues, find relationships between columns, and understand
data-profiling
data-exploration
data-analysis
data-visualization
DataWeigher: Data Profiling & Exploration Tool
DataWeigher is a data profiling and exploration tool that allows users to quickly understand data by analyzing statistics, distributions, relationships and more.
What is DataWeigher?
DataWeigher is a powerful yet easy-to-use data profiling and exploration software. It allows users to quickly understand the contents of their data by automatically analyzing statistics, distributions, patterns, relationships and more. Within minutes, DataWeigher can profile millions of rows of data and generate interactive visual reports to:
- Identify data quality issues and outliers
- Understand data distributions and variability
- Find functional dependencies between columns
- Detect numeric patterns and calculate statistics
- Identify text patterns through NLP techniques
- Suggest transformations to prepare data for analytics/ML
DataWeigher was designed for everyone from data analysts and scientists to database developers and business users. The intuitive drag-and-drop interface makes it easy to import data from 30+ database and file formats, profile any size data, and share interactive reports with recommendations for how to improve data quality. Advanced features include custom data rules, data masking, export options, and more.
In summary, DataWeigher saves significant time in understanding and prepping data for downstream initiatives. Companies use DataWeigher for faster analytics cycles, reduced costs of poor data quality, better access to data insights, and increased data literacy across teams. Its ability to handle large datasets while keeping things simple for all users is what sets DataWeigher apart.
DataWeigher Features
Features
- Visual data profiling
- Column statistics
- Column distributions
- Column relationships
- Customizable reports
Pricing
- Open Source
Pros
Easy to use graphical interface
Fast data analysis
Integrates with multiple data sources
Open source and customizable
Cons
Limited transformation capabilities
Less support for unstructured data
Steep learning curve for non-technical users
Official Links
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