Missing socks in the washer/dryer. A mystery that no one really knows or has figured out. One wonders where they go since most are never seen again … makes us treasure a pair of matching clean socks since they may be rare depending on when laundry day is that week.
Now, I am guessing you are wondering how this can possibly be related to clean data. You also may be wondering what the heck does “clean data” mean? To explain, it may help to provide a comparison between “poor data” and “clean data” using four categories:
- Irrelevant/Relevant Data
- Inaccurate/Accurate Data
- Inconsistent/Consistent Data
- Incomplete/Complete Data
What if we told you some clean data facts:
- Only 5 percent of raw data is really significant/relevant, which leaves the remaining 95 percent deemed irrelevant
- An average CMDB is only 50 percent to 75 percent accurate – again leaving the remaining percentage inaccurate
- Inconsistencies abound since multiple entries for a single piece of software are often found
- Data is often incomplete in that key data points are missing (version, release dates, end-of-life (EOL), etc.)
Unfortunately, these are the characteristics of poor data, which may make some of you a bit uncomfortable. Realizing that you might not really know what you have. And you can’t truly manage what you don’t know. No one likes to be surprised in this way since people normally don’t like the possible idea of failure. There I said it – one of the “F” words. In this case, shedding light on poor enterprise data means you can do something about it.
The goal is to get clean data. Data that is up-to-date, doesn’t have duplicates, is consistent, and complete with additional relevant information. Complete, clean data can be achieved by enriching the data with relevant market data points that help in the identification and maintenance of devices in an enterprise.
Clean data enables enterprises to make better business decisions that can affect strategic planning and investments. With clean data, enterprises can improve their response rate, which can impact both revenue and customer and/or shareholder satisfaction – fundamental components to any successful organization.
If you want to read more about clean data, download the white paper “New Technology Leader: Driven by Data”. It was written by Don Jones, a Microsoft MVP, who shares his insights on how data affects enterprises. It’s a good read, especially in a clean pair of matching socks.