Many large organisations struggle to manage their IT architecture because they do not understand what data the Business relies upon and in many cases, the Business doesn’t fully understand it either!
The symptoms of the above can usually be translated into substantial increase in storage requirements, performance degradation, unmanaged data quality levels, limited understanding of the impact that IT changes may have on data and also, quite importantly, increased exposure to breaking legal and regulatory requirements.
Even though data should be an enterprise asset, it can be perceived as limiting the organisation if not appropriately managed. Below are key points that all organisations need to address to successfully manage their data:
Know what data you rely on
- Create a data dictionary, expressed in Business terms not “database language”, to identify what data the organisation relies upon.
- Understand how critical the piece of data is to the organisation and how accurate it is.
Know where the data lives and how it is used
- Understand what applications store/update each data element.
- Understand how the data is distributed between the applications.
- Understand what business capability/process the data enables.
Know where the data lives and how it is used
- Understand what applications store/update each data element.
- Understand how the data is distributed between the applications.
- Understand what business capability/process the data enables.
Know who (should) owns the data
- Identify who in the Business owns what data.
- Identify who in IT own what application and the data that the application manages.
Manage change in data
- Understand impact of IT or Business change on data.
Manage data lifecycle and data security
- Actively manage legal & regulatory requirements, data retention and data access controls.
IT leaders are constantly asked to do more with less, further enabling their organisation whilst reducing IT expenditures. Technical architecture is like a big puzzle with many moving parts and dimensions with one common thread between the pieces of the jigsaw: data. It is therefore paramount that this is not left unattended, free to “roam” uncontrolled through the IT landscape, or the requirements set upon IT leaders can never be met.
Data Architecture and Data Governance driving goals are precisely to help achieve the above.
