Data Mashup, Mashup Tools, Enterprise Data Mashups

Data Mashup

MetaDash's data mashup technology is the foremost tool for both designers and end users who want to bring together disparate data from multiple sources. Moreover, its built-in machine learning engine enables the mashup of machine generated intelligence with human intelligence, bringing data mashup to a new level.

Professional Data Mashup & Governed Self-Service Mashup

BI professionals can not only easily mashup disparate data into analytic data blocks, but they can also enable controlled self-service data mashup for users via data models. Data models map prepared data to business terms and completely shield end users from underlying technical details. Data blocks' built-in visual transformation and data cleansing functions make data preparation effortless with minimal technical skills.

Models' built-in governance enforces data consistency and safeguards data processing engine integrity. As part of data governance, the data security model can secure data down to the cell level where users will only access their personalized data.

More About the Data Mashup Driven BI Web App

Data Mashup and Visualization - Mutual Helpers

MetaDash's data mashup capability is tightly coupled with visualization as one web app. Mashup users can quickly profile and verify data blocks with visualization. The web app can be used the other way as well. While creating a visualization, mashup is used to refine data blocks. Because of fine-grained control, power users can utilize these functions up to their skill levels.

Interact with Mashup Powered Dashboards

Compressed, Cluster Ready, In-Memory Cached Data

MetaDash's data mashup engine results in highly flexible data blocks. A data block can either pull in data from data sources in real time or be set up as a high performance cache. Cached data blocks are compressed and optimized for in-memory operations. User actions are served by in-memory calculations performed at lightning speeds.