January 05, 2009, 8:28 PM — The maturity scale for IT data management is an attempt to shed some light onto the event and information management markets. Especially on log management, security information and event management, and some of the advanced analytics space. By using this scale, there are a number of conclusions that can be drawn, most notably that the security visualization or IT data visualization market is currently fairly complicated and small.
[ This post is a summary of a longer discussion of the Maturity Scale for IT Data Management. ]
Figure 1 shows the maturity scale. Any company or IT department/operations can be placed along the scale. The further on the right, the more mature the operations with regards to IT data management. A company generally moves along the scale. A movement to the right doesn't just involve the purchase of new solutions or tools, but also needs to come with a new set of processes. Products are often, but not always, necessary.
The further one moves to the right, the fewer companies or IT operations can be found operating at that scale.
Figure 1: IT Data Management Maturity Scale.
Figure 2 encodes a few properties along the same maturity scale: number of products on the market, number of customers/users, and number of data sources needed at that state of maturity.
Figure 2: The number of products, companies, and data sources that are used/available along the maturity scale.
Why are so few products on the right side of the scale? Or asked differently, why is there no advanced visualization tool that we could use for visualizing security data or IT data in general? The most obvious reason is one of market size. There are not many companies on the right side. Hence there are not many products. Why are there not more companies close to the advanced analytics stage? Here are two reasons:
- Not many environments manage to collect enough data to implement advanced analytics across heterogeneous data.
- A lack of qualified people (engineers, architects, etc)
There are a number of other conclusions that could be drawn from the scale. Have a look at the original post to see some more details.