Data Quality Management
Supercharge productivity and fast-track the path to analytics.
Perfect Your Data With Ease
The best decisions require with the best data. But manually understanding data health and completeness, and then making corrective changes to it is often error prone and resource intensive. Alteryx provides built-in data profiling, data quality tools for cleansing and collaboration that supercharges productivity and fast-track the path to analytics.
Built-in Data Profiling Power
Data profiling enables analysts and business users to quickly and visually assess the statistical health, completeness and quality of a dataset to ensure that is ready to confidently make decisions on―or if it requires additional cleansing and enrichment.
- Visually assess data health – See the statistical distribution of the dataset, as well as a grading of data completeness
- Identify granular data issues – See profiling graphs showing data quality of each columns based on different data types.
- Profile any data– Whether from data warehouses, cloud apps, spreadsheets and other sources, all in a single platform
Intuitive Enrichment and Data Quality Tools
Don’t waste valuable time trying to cleanse data in spreadsheets or with custom code. Alteryx provides a complete range of drag-and-drop data cleansing, standardization, fuzzy matching, and enrichment tools that free resources and improve data quality.
- Quickly enhance and cleanse – Over 45 tools to eliminate nulls, cleanse, investigate, and standardize a dataset
- Fuzzy matching – Easily implement fuzzy matching techniques to manage non-identical duplicates based on adjustable parameters
- Enrich data – Blend in supplemental or third-party datasets to improve quality such as adding more spatial, demographic, or customer data
Collaborative Data Quality Management
Take data quality to the next level with collaboration and reuse. Alteryx centralizes metadata, information assets and mappings to minimize inconsistencies. And with Alteryx Connect, teams can rate and certify assets, and get complete transparency through data lineage.
- Repeatability and reuse – Share, reuse and version workflows, mappings, visualizations, data science models to improve data consistency and accuracy
- Collaborative data quality management – Use Alteryx Connect to annotate, discuss, and rate workflows, data sources and artifacts
- Certification and data lineage – Data and workflow certification and lineage with metadata graphing that shows inputs/outputs all improves trust and transparency