Data Management Services

In today’s competitive age, business needs are dynamic and ever evolving therefore pushing enterprises to adopt newer applications and to upgrade existing systems. This often results in the need to migrate critical business data. It is crucial that this data is managed accurately while ensuring minimal business disruptions and avoiding common problems such as multiple and disparate data interpretation.

RECYKLA Data Management Framework helps organization to improve the accuracy, entirety and aptness of information assets. We provide data quality assessment, implementation and monitoring services. Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise.


  • Lack of centralized Metadata management.

  • Non-integrated processes and information.

  • Higher security issues with uncontrolled and/or unauthorized access to data.

  • Intricacy in managing data to get right information at right time.

  • Jumbled internally- and externally-generated data.

  • Increasingly difficult storage of high volumes of data.

  • Complexity of collecting, managing and distributing data.

  • Unstructured data leading to higher expenses.

What RECYKLA Offers

RECYKLA’s data management services include planning for data management transformation, master data management, data architecting, operating model definition, system integration, data governance, metadata management, data mart consolidation, data quality management, and Customer Data Integration.

Our comprehensive Enterprise Data Management Framework can help client with the following:

  • Identify, implement and maintain a single, unified view of reference data across the enterprise.

  • Ensure data security, through security policies and processes.

  • Establish processes that ensure good quality data on a regular and consistent basis.

  • Define and implement data architecture encompassing data modelling, data flow analysis, tuning, storage, visualization and infrastructure.

  • Achieve organizational alignment on the governance of data management issues throughout the enterprise solution.

  • Redesign of database schema, stored procedures and functions.


  • Controls data redundancy.

  • Automatic and intelligent backup and recovery.

  • Central repository to store information.

  • Transfer of business intelligence data such as business critical reports, waste management of products at the end-of-the product life cycle reports, dashboards, scorecards and analysis.

  • Customized reports providing information as needed.

  • Right information to the right people at the right time.

  • Proper and appropriate security levels with segregated user rights and role-based accessibility.

  • Calibration of new applications.

  • Real time data management solutions.