In todays data intensive environment, it is a challenge to manage and exchanges data across disparate systems.
The data can be stored in dissimilar formats such as databases, text files, XML, word, and excel documents.
The organization need to effectively manage, unify, and communicate these data in real time to get the competitive edge.
DataGlance Framework enables the company to manage and exchange data through a single integrated product suite.
It provides the ability to effectively manage the data growth, support data conversion/migration/upgrade, integrate data from
different sources in a standard format, and exchange information in batch, real-time, and event driven process.
DataGlance Framework also enables the user to combine virtually any data (including unstructured data) and build flexible
solutions to meet current and future needs.
DataGlance Framework provides a comprehensive Enterprise Data Management platform that can effectively manage enterprise wide:
- Data Conversion/Migration
- Data Subsetting & Masking
- Data Profiling
- Data Quality & Validation
- Data Cleanup
- Data Growth (Archive/Restore)
- Data Integration
Metadata Driven Architecture
- Complete design, development, and deployment framework based on metadata.
- Metadata stored at product version level. The metadata is used to describe data model that represents a Business Entity.
- Application based approach rather than data based approach.
- Code free solution based on metadata.
- Solution built independent of data sources. The data is extracted, transformed, and loaded using Business Entity independent of the underlying data source.
- Leverage same metadata to build multiple solutions.
- Extensive "Where Used Analysis" to support Auditing and Compliance.
DataGlance Repository used to store metadata information at product version level.
The metadata management provides easy user interface to manage and update metadata.
It provides a comprehensive where used analysis tools to analyze different data elements used across each solution and its change effect.
DataGlance Framework is built on innovative modular design. The modular metadata driven design enables the separation of business logic from technical implementation.
The solutions are build on top of Data Models that presents how business data are stored within each Application. A Data Model can represent a Business Entity.
The Business Entities are used to build solution to meet data growth, support data conversion/migration, profile data for quality and validation, expose as web service and generate reports.
The solutions are build independent of how the Business Entity data is stored (database, XML, flat file etc.).
The business rules can be applied to each solution. The business rules defines what and how the data should be processed. It can be applied in three different styles: message based, event based (including messages), or data based.
Define Once Approach
The modular design approach allows the user to define a Business Entity once and use in multiple solutions.
The Business Entity can be represented using an XML Schema or Object relationship within the database.
The metadata information is stored in a Repository.
The model representing the Business Entity can be used to build any number of solutions to convert, migrate, profile, or integrate data in batch or real time.
The solutions are built independent of the data source that will be used to read or write the data.
The data sources can be switched without making any changes to the Business Entity or Mapping rules.
LIVE Data Transfer
DataGlance provides the capability to perform live data conversion, migration, and upgrade. It is supported by built-in trigger capabilities, polling mechanism, message, or service oriented implementation.
The data transfer is performed to maintain data integrity.
Reduce Data Conversion/Migration Downtime
DataGlance provides the capability to convert/migrate data in stages reducing Application downtime.
The business rules can be setup to transfer data in multiple stages. For example, the static data can be transferred before dynamic data.
The static data can be transferred without taking the source and target application down.
This helps reduce the downtime required to convert/migrate any product.
Easy of Use
DataGlance product is completely web based with no client installation. The application is launched using a Web Browser.
All solutions are built using an easy to use drag and drop user interface.
A Relation Data Mapper is used to define rules to develop conversion, migration, and interface rules between Object, Data Model, and Business Entity.
A single management console to manage and monitor processes.
DataGlance Framework is designed to work with any database that supports JDBC or ODBC driver. The data viewer can be used to view data from any supported database
from a single user interface with no client installation.
The data viewer can also be used to view XML data or data in delimited file format.
The Data Viewer can be used to simultaneous connect to multiple data sources to support data comparison.
DataGlance Framework supports different data sources and data in different format.
- IBM DB2 (Open and Main Frame)
- MS SQL Server
- Lotus Notes
- Any other databases with JDBC and ODBC drivers.
- Flat Files (include XML data).
- Message Queue (MQ-Series and JNDI based)
DataGlance products are web based installed under an Application Server. It supports all Application Server that supports Java v1.5
and Servlet API. It can installed on any platform that supports Application Server with the required support.
- IBM AIX
- Sun Solaris