Data Management Services


Data management is the development and execution of architectures, policies, practices and procedures in order to manage the information lifecycle needs of an enterprise in an effective manner. It is the process of controlling the information generated during a research project. Any research will require some level of data management and funding agencies are increasingly requiring scholars to plan and execute good data management practices.
Managing data is an integral part of research process. It can be challenging particulary when studies involve several researches and/or when studies are conducted from multiple locations. How data is managed depends on the types on data involved, how data is collected and stored, how it is used - throughout the research life cycle. Effective data management practices include :

  1. Designating the responsibilities of every individual involved in the study.
  2. Determining how data will be stored and backed up.
  3. Implementing the data management plan.
  4. Deciding how data will be dealt with through each modification of the study.

Data Management Life Cycle




  1. Dedicated Data Architects.
  2. Specialization on Data Architecting & Modeling, Data Integration, MDM & EDW.
  3. Standards Exposure to IBM BW Reference Data Model.
  4. Exposure to Teradata Data Warehouse.
  5. Data Archiving through Document Management.
  6. Data types – Text, Voice, Images, Video, PDF, Biometrics, Wave Form Data.

Technical Approach



ETL Systems


Extract, Transform and Load Systems are commonly used to Integrate Data from multiple Applications typically developed and supported by different vendors or hosted on separate computer hardware. The disparate systems containing the original data are frequently managed and operated by different emloyees. ETL Systems :

  1. Extracts data from outside sources.
  2. Transforms it to fit operational needs, which can include quality levels.
  3. Loads it into the end target.

ETL Development Life Cycle



Approach to ETL Testing


DBA Services


Production Glimpse


Key Responsibilites

  1. New Database Setup
  2. Database Versions upgrades
  3. Database Migrations
  4. Monitoring and ensuring environmental availability
  5. Fix Issues
    1. Database Server
    2. Patches
    3. Backup failures
  6. Performance issues
  7. Backup and Restores
  8. Executing DML Script

Database Supported

  1. SQL Database (2000, 2005, 2008,2012)
  2. Oracle Database (9i, 10g, 11g)
  3. Oracle Apps DB (R12)
  4. Sybase 10
  5. UDB DB2 / Mainframe DB2
  6. MySQL
  7. Trained on Teradata

Key Characteristics

  1. 24 X 7 Coverage Offshore / Onshore
  2. Knowledge Base & and Standard Operating Procedure driven
  3. Stringent SLA for
    1. Response & Resolution
    2. Quality –
      1. Communication
      2. Attention to detail
      3. Time to resolve technical proficiency