The Unifi development team has just delivered version 1.11 of our industry-leading, end-to-end data integration platform. Loaded with new customer requested features, operational refinements, performance enhancements and enterprise management and operationalization improvements, the latest version further differentiates Unifi Software from other offerings in the emerging self-service data integration space.
Unifi is the only data integration platform that combines comprehensive data discovery tools with feature-rich and performance-optimized data preparation tools for the business analyst. Based on a request from one of Unifi’s customers, specifically a global media and entertainment client, version 1.11 has significant advances in the area of Metadata Management & Search. The Unifi platform provides automated metadata profiling to facilitate discovery and normalize data attributes across the organization. For example, if one infrastructure element calls an attribute Stream_Initiate and another part of the system calls the same attribute Video_Play these can now be linked automatically in Unifi saving hours of manual processing or offline ETL programming to achieve the same results. Any customer who is combining legacy data sets with new systems where attribute naming conventions have inconsistencies will immediately see the benefit of just this one aspect of Unifi’s data discovery tools.
Another unique feature of our Metadata Management & Search ensures that information about the data is stored together with the actual data. This helps business analysts understand the data definition in a very informative and intuitive way. Comprehensive social aspects of the Unifi platform delivers cross-functional and organization-wide learning, collaboration, sharing and metadata scoring, i.e., rating the accuracy of the data and metadata information. This leads to enterprise-wide information enrichment over time.
Other major aspects of Unifi Software version 1.11 are performance enhancements and IT operationalization, including Profiling & Full Stats Collection. Now Unifi leverages the in-memory performance of Spark for profiling and collecting full stats for datasets on HDFS. This provides business analysts with the ability to profile and understand information about their full datasets. The release enhances how Unifi utilizes the combined power of in-memory computation through Spark and regular computation through MR/Hive.