The New Face of Data Discovery
We all use some form of analytical tools but do they satisfy our appetite for self-service access to data?
While faster reporting intervals might be able to match the pace of operational activities,
this does not satisfy the need for most of us to develop our own questions and quickly see the data to get the answers we need now.
Furthermore, we can't predict in advance what data we will need to make business decisions or support operational activities.
See how your business and technical colleagues can work together. Step up to the next level of data analysis.
Cataloging/inventorying data assets and tagging/annotating data for exploration, discovering data lineage and recognizing patterns in business data.
Query forming, data blending, filtering, user-defined calculations, and data augmentation.
Modeling business data from conceptual level down to logical models and discovery of relationships among data source attributes.
Sharing data source connections, sharing queries, sharing datasets, and publishing data models.
Cataloging metadata, data sources, data source attributes, lineage, relationships and other relevant metadata.
Harmonizing disparate data sources to provide unified data for business analysis, reuse and maintaining data quality.