Groundwork for effective project data management
Maintaining project data is essential for proper and effective project management. Without maintaining the project related data it is not possible to see even the progress of any project and the expenses made so far on that project. Lot of work on projects depends on the project data that is managed in a system.
Data management policies should be drafted to manage project data. All those who are using the project should be aware of the policies in place and act accordingly. It is better to have a manager for managing data related issues that may surface in the future. The different data types used in the project should be defined prior to using such data.
A research should be made to find out the different data types that are used in the project. Apart from the type of data, the volume of such data expected to be stored in the database during a project should also be estimated. Format of data to be stored should be finalized so that it will be easy to covert from one format to another if needed in the future.
In case of data that is fed to the system in real time, proper calibration of the instruments is to be done prior to implementation. All the real-time information is to be documented so that they can be referred to, to find any criteria at any instant. The quality of the data that is fed to the system should reliable. For quality data there should be responsible person who ensures that the data fed is reliable. Tools should be developed to find out any irregular data from the system. Changes made to any data should be well documented and related metadata should be updated.
The other decision to be made with respect to project data management is to decide whether to store the data in a centralized database or a distributed database. Both of them have their own advantages and disadvantages. You can analyze your pattern of project work and your business requirement and then decide whether to go for centralized or de-centralized database.
| Choosing an effective data management solution | Different components of a data management process | Effective data management strategies for your organization | Features to look for in product data management software | Groundwork for effective project data management | How to implement a product data management system effectively | Outsourcing your work to professional data management services | Preferred storage for life cycle data management | Pros and Cons of distributed data base management system | Tiered storage and data lifecycle management | Understanding data management concepts | Understanding data management definition | Using the right data management techniques to increase efficiency | What are the data management best practices to follow | What do you understand from the definition of data management | What is data base management | What is product data management |
Monday, November 30th, 2020
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