Enterprise Data Management

Use Case

Digital Transformations/ Cloud transformations
Business Mergers, acquisitions or divestitures
Data Assessment - know what data there is, where it is, and its quality
Data Cleansing to improve data quality & decision making
Data Harmonization across applications
Building data pipelines for moving data across the enterprise - to serve discrete business functions
Govern your data catalog across an enterprise - putting in controls for data creation & quality
Visualization, analytics & reporting on the data in real-time, with user-friendly dashboards
Cataloging data so that all data is accessible to day to day users

Save 40 to 70% in time & cost of managing enterprise data
Reduced manual effort in cleaning, governing, reporting on and searching for data
Repeatable, Scalable & Agile process. Can be repeated for multiple businesses.
User-friendly screens, with a humanized UI
No-code / low-code approach data management software
A full 360-degree view of Customers, Suppliers and Products provided all the insights for Sales, Service, and other functions.
A centralized EDM ‘data lake’ becomes the singular golden record for data across the enterprise
C-Suite dashboards to provide C-level execs with information need, when they need it
Data Quality improved by over 40% in the first three weeks to get to 99% accuracy.
Data Catalog improves trust in the EDM data and establishes a baseline for all custom development work.
The implementation of EDM management accelerates the implementation of new cloud solutions, equating to approximately 40% cost savings

Pay-as-you-use data analytics tool
Certified Platform for Oracle, SAP, Microsoft, Salesforce & IBM.
Ready to use 9000+ Templates that automate data quality, extractions, loads, transformations, reconciliations, mappings, MDM & governance.
Inbuilt Patch Analysis engine, helps to retrofit any changes to the Templates for new versions on cloud.
Easily Configurable - a no-code approach that saves upto 70% in time
Highly Scalable to accommodate large data volumes
Parallel processing
Cloud First, Ease of use