EDM ANALYTICS-AS-A-SERVICE
WHAT IS DM/EDM RESPONSIBILITY
Process of inventorying and governing your business’s data and getting your organization onboard with the process.
COMPONENTS OF DM AND EDM
IDENTIFYING A CRITICAL SKILL
Data management requires data management technologies, data security mechanisms support and quality assurances.
Key Factors involved in Drivit’s EDM Process
Drivit’s successful Data Management process key factors include:
- A data architecture is designed and deployed with several repositories for organization’s data
- Better understanding of operational performance and Business activities
- Analysis of patterns and understanding the impact of strategies implemented
- Interaction with custom data and scenario prediction
- Significant interpretation of a large volume of data
- Process optimization and decision-making based facts
- Increases productivity
Best Practices of Drivit’s EDM Service
For EDM service to be best in practice, Drivit focuses on adopting:
- Drivit allows an effective data management deployment in IT systems that run business applications and provide analytical information to help drive operational decision-making and strategic planning by corporate executives, business managers and other end users.
WE HELP YOU
- Managing and integrating data architecture in a coordinated way
- Managed services must be monitored closely to make sure data processing bills don’t exceed the budgeted amounts
- Data managers need to help ensure compliance with both government and industry regulations on data security, privacy and usage
Drivit’s EDM Services
It is the process of providing the following services:
How Drivit is managing the data?
Drivit’s data management involves a variety of interrelated functions:
- A data architecture is designed and deployed with several repositories for organization’s data
- Modelers create a series of conceptual, and physical data to map workflows so that information can be organized to meet business needs
- Data from different transaction systems and other sources is integrated in data warehouse or data lake for analysis
- Data quality checks are done to identify data errors and inconsistencies so they can be resolved via data cleaning
- Data governance is an organizational process that creates and manages data governance policies to ensure that data is consistent