Information is one of the most valuable assets of any organization. However, often it is stored into multiple older and newer systems or the business and IT communities have different views on how to manage it. This leads to difficult situations when there is a need to turn the information into knowledge, but all the organizations have are disparate sources of data.
LifecycleDM is a comprehensive data management solution, which helps organizations govern their information assets. Some of the advantages of the product include:
- Including a comprehensive metadata model, LifecycleDM allows describing the data sources in the organization and their structures within a single Metadata Repository. This concentrates the knowledge about the information and allows for centralized definition and monitoring of the various management activities.
- In addition to the technical parameters of the data, LifecycleDM maintains business-oriented attributes such as subject areas and user-friendly names in multiple languages for any information object. This merges the technical implementation and functional documentation, allowing great improvement of the communication between the different tiers of the organization. Combined into a web-based interface, the knowledge is made available to the IT support personnel, the business users and the management to share and develop.
- LifecycleDM allows definition and maintenance of hard and soft constraints over the sources – an automated solution for enforcing integrity and quality of the enterprise data. Continuous monitoring is possible via control statements and KPIs delivered through web-based dashboards and e-mail notifications.
- Extraction of data based on control statements for erroneous data, manual modifications or transformation using predefined tables of correspondences, and loading the clean data back into the original enterprise systems.
- Extraction of data from legacy data sources, transformation according to the new requirements, enforcing integrity and quality without losing data, loading into the target system, process monitoring and reporting.
- Scheduled extraction, transformation and loading from disparate data sources. Organizing data into multiple subject areas and assigning business oriented terms to the data entities. Different methods of keeping data – full history or full refresh. Time-based partitioning of the data providing better performance. Pre-aggregating data for reporting and analysis.
- Following regulatory and internal business policies, but still managing the storage costs is a major concern for organizations. LifecycleDM allows defining archiving data flows and performs scheduled data movement into archival databases stored on low-cost devices. It is also easy to extract back the data when it is required during audits or in other situations.
- An overview of the system based on Key Performance Indicators (KPIs) and preview of the latest events.
- One-click search within the system metadata.
- User Profiles and Security - users, groups and privilege management.
- Connectors – configuration of the access to data sources and targets.
- Loading the structures of the source and target objects into the Metadata Repository.
- Management of new and existing tables/views/materialized views and other database objects – primary keys, foreign keys, hard and soft constraints, indexes, partitions. Classifying data entities into subject areas and assigning business-oriented descriptors.
- Synchronization between metadata models and physical structures and between different metadata repositories – for example in development and production environments.
- Definition of mapping-based business rules and transformations via the Transformation Builder.
- Data maintenance configuration – loading, transforming, archiving, cleaning up data. Managing automating time-based table partition creation.
- Collaboration – messaging, notifications, document sharing.
- Configuration of scheduled jobs, steps and tasks for performing data management activities such as transformation, archiving and validation.
- Data control – control statement and KPI definition for monitoring data integrity and quality. System (based on data constraints) and custom (query-based) control statements.
LifecycleDM’s architecture is based on the concept of integrating the data processing engine into the relational database management system. LifecycleDM consists of two main components:
An Oracle database containing metadata about:
- Data sources, their structure, technical and business attributes
- Job execution
- Mappings and transformations
- Data control
- Users and privileges
- Messages and collaboration
- Implemented as Oracle PL/SQL packages, it benefits from industry standard data access and processing foundation. From the metadata definitions, the Engine produces DDL and DML SQL statements, which are executed against the host Oracle database or against the sources via database links.
- J2EE application featuring a Hibernate-powered ORM layer for managing the Metadata Repository, and presentation layer based on JavaServer Faces (JSF).
In 2007, Société Générale Expressbank (Bulgaria) has migrated to a new core banking information system. As part of this project RCC Solutions deployed LifecycleDM as part of the Report Express system for daily extraction, transformation and loading data from the core banking system’s database to a database specifically designed for the needs of regulatory and management reporting. LifecycleDM is also used to ‘feed’ other systems directly by loading data into their databases, or through the generation of interface files.Back to top
Hardware Intel x86-compatible 32/64 bit
Operating System Windows / UNIX / Linux
Database Server Oracle 9i / 10g
Application Server Any J2EE Application Server (BEA WebLogic, Tomcat, JBoss or other)
Web Browser Modern web browser on any platform