Databases Reference
In-Depth Information
●
What are the associated metadata and master data that need to be processed with the data to be
retained?
●
What data will be archived?
●
Data security: What are the user security and data security requirements?
●
Metadata: What taxonomies will be needed to manage data?
●
Business rules: What are the tools and associated business rules for processing?
●
Data stewardship: Who owns the data type?
●
Documents—legal, HR, finance, and customer service are all business units to consider
●
Videos, audio, and images
●
Email
●
Call center
●
Social media
●
Content management data
●
Audit, balance, and control:
●
What data needs to be audited?
●
What data needs reprocessing in failure situations?
●
External data integration:
●
External taxonomies can be integrated to process additional hierarchies and master data
enrichment in processing Big Data. You need to understand the granularity and hierarchy of
the external data.
●
Third-party data from agencies can be integrated to create reference data and lookup data.
●
EDW integration:
●
Data extracts to the data warehouse need to be defined.
●
Metadata integration with the enterprise data needs to be managed and monitored.
●
The integration refresh cycles need to be defined.
●
Data structures to store the Big Data need to be defined and implemented.
Program governance
A strong framework for managing the projects and the people pillars forms the crux of program gov-
ernance. While there are no significant differences in program governance approaches, the following
can be extended:
●
What projects are currently being driven to enable information life-cycle management?
●
Who are the teams that are assigned to the different programs?
●
What is the cost of the implementation for each cycle for each project?
●
What are the risks and identified mitigation strategies?
●
What are the critical areas that need executive alerts?
●
What are the critical priorities and the impact of changes to the priority to the program schedule?
●
What are the budgetary constraints that impact the program?
Processing
●
The data acquisition process in the world of Big Data has no predefined process. The audit process
framework needs to be extended to include Big Data processing. The audit data will consist of the
file name, date of process, size, and source (if available).
●
Data processing in the world of Big Data contains no predefined schema to model and load
the data. In this situation, extra attention needs to be given to metadata management. There
