Intel Open Port: IT@Intel Blog : Tags : data

In the world of effective software inventory management there are audits. Those audits are done comparing the software to physical installations or against budget. There are audits performed when a HFE (Human Factors Engineer) analyzes your usability or those done to ensure that you have sufficient disaster recovery elements in place.

This happens every day against dozens of software applications and I have to ask the question -- where do you record this data? Does everyone have individual approaches and simply has a spreadsheet containing the data? Is it recorded anywhere?

I have to wonder where the value is in gathering data that has no reuse or exposure to the owners of the software solutions.

So I've been bouncing around an enhancement to allow certain groups to register (and report) on audits. Internally some people hate it and some love it.

What do you do?
Do you have yet another application for capturing software audits?
Do you do them at all?

Let me know.

Previous topics include Application inventory, what do you capture?, Application inventory starts with a definition, Application inventory as a cost savings initiative, Application Inventory, the start of data sustainability? and How do you measure data quality in your Application Inventory?.

2 Comments Permalink Tags: application_inventory, data_quality

It is vitally important to give data consumers an indicator of the quality of your information. This helps to build a trust in the completeness and review state related to what they are consuming. What we have implemented is real-time, includes embedded business rules and a pretty little display.

So what did we do?

Created a Five tiered rating system Data Quality(DQ) State
Moving through each tier means that data completeness and audited quality checks are performed
As the software application moves through its life cycle, additional data elements become mandatory, which effects the dynamically calculated rating
DQ State value exposed for interfaced consumption
Shown on-screen with graphical representation

What is involved in each DQ State tier level?

DQ State 0: does not meet minimum required data
DQ State 1: Name, Business Description, Status, Manufacturer, Owner (Group/Contact)
DQ State 2: State 1 plus - Host, Software Type, User (count/location), Data Classification, Technology categories
DQ State 3: State 2 plus - Cost Assessment
DQ State 4: State 3 plus - Capability categories, Network communication details, Business Continuity details

This tiered approach begins to define higher quality for the data completeness as it moves up the defined levels. Not only having the blanks filled in, but the application of embedded business rules-based analysis to validate content, drives the state calculation. These are updated based on any change to any of the evaluated content.

What do you do in your organization? How do you ensure that the data "freshness" is preserved?

Previous topics include Application inventory, what do you capture?, Application inventory starts with a definition, Application inventory as a cost savings initiative and Application Inventory, the start of data sustainability?.

2 Comments Permalink Tags: value, software_development, application_inventory, cost_savings, data_quality