Zaloni’s new Mica release makes data discovery, curation and self-service data preparation more collaborative and intuitive for business users
San Jose, CA – March 30, 2016 – Zaloni, the data lake company, released today a new version of its Mica self-service data preparation platform at Strata + Hadoop World. Mica provides users with an on-ramp for self-service data discovery, curation, and preparation of data in the data lake. With Mica, business users have the tools they need for rapidly discovering data sets, interacting with them and uncovering needed business insights.
According to a January 2016 report, entitled Overcoming Obstacles That Prevent the Deployment and Use of a Modern BI and Analytics Platform, Gartner predicts that by “2017, most business users and analysts in organizations will have access to self-service tools to prepare data for analysis.”
“Data preparation can no longer exclusively be an IT function,” said Ben Sharma, Zaloni’s co-founder and CEO. “There’s too much data and too much demand for immediate access to that data as data-driven organizations turn to analytics to improve their businesses. Also, many enterprises find that business users often get better results faster because they have a deeper understanding of the data. Modern enterprises that want to derive more value from their big data need to use a self-service platform like Mica to democratize access to data for business users and enable greater responsiveness, agility and increased collaboration.”
Mica leverages Zaloni’s award-winning Bedrock data lake management platform for metadata management to ensure data quality and to provide a workflow engine to automate data transformations for any relevant incoming data. Many of Zaloni’s Bedrock customers have added Mica to their technology stack.
“We are an analytics-driven company,” said Mike Esler, head of data services at Avant, a leading provider of online lending. “Zaloni’s Bedrock and Mica data lake management solution will provide the visibility, transparency and democratized access to data that we need to progress the advanced analytics use cases that support our business.”
In addition to its core functionality, which includes an enterprise-wide data catalog, a self-service data preparation sandbox and seamless workflow operationalization capabilities, the latest release of Mica provides additional features to further improve user productivity:
- Shared workspaces – Enables teams to collaborate to increase productivity. A workspace includes entities hand-picked by a team member and shows the history of enrichments/transformations done to those entities; team members can share their enrichments and entities of interest with peers and build on each other’s work.
- Entities ratings – Allows data stewards and business users to add and update business context by providing labels, descriptions and ratings to data sets. This can help business end users get better context and search results when using the data catalog.
- Customization – Provides ability to customize themes, content, logos and home page to meet enterprise brand standards; bookmark other useful data management or governance tools within Mica’s menu.
- Enhanced metrics – Tracks the makeup of your data lake with entity-level usage metrics (e.g., record count, number of files, total size); field-level data quality metrics (e.g., field frequency of values, nulls); and profiling metrics at entity level and/or at field level.
- Smart searches – Updates workspaces automatically and in real time with new entities that meet established search criteria; create searches and save criteria so other users can re-run the criteria without needing to re-filter.
- LDAP integration – Configure and use LDAP (Lightweight Directory Access Protocol) for secure user authentication.
“Providing business users with visibility and access to data across the enterprise ultimately helps enterprises get more value from big data by making it easier to discover and prepare data,” said Sharma. “We’re excited about the Mica enhancements because they provide additional “smart” automations for faster data preparation and make the business user experience even more intuitive and relevant.”