Why Data Management Matters
Data collection is the foundation of all capacity planning, but managing that data is just as important as the way you’re gathering it in the first place. How you choose to do this will depend on your business, but there are some practices that always will serve your purposes.
Your data can be your best friend or your worst enemy — it all depends on how you manage it. If your data management strategies are ineffective, your collected data is useless. Some place the domestic costs of misallocated data at an astounding $3 trillion annually, according to SYS-CON. When calibrated correctly, though, your data gives you the ability to analyze past performance trends to predict how you should act in the future.
This kind of analytical power can boost the productivity of your business and cut superfluous costs. But the way in which you manage your data is driven by the results you want.
There are hundreds of ways to collect performance data, but the goal is always to create a well-stocked “performance data warehouse.” And the questions you want to answer will always be determined by your “filing system” — the way you store your data for future analytical use.
More specifically, different granularities of data (durations of a collecting period) are needed to field different answers to different questions. If your company provides sophisticated FinTech that aids in day-trading, you need very precise data, and will likely keep data records for every single second of up-time. But if a consulting firm wants to track their IT system usage over one year, collecting data points in one-minute periods may suffice.
As time goes on, that one-minute dataset may not make sense — to track progress over years of use, data periods of 15 minutes or even a full day may be appropriate. This strategy allows your data to be summarized and stored as an aggregate to answer more general questions.
You can also store parallel datasets if you have multiple, simultaneous data collection needs. For instance, companies can collect one-minute data points alongside 15-minute points. At the end of your aggregating period, you’ll have a much better picture of which granularities are the most useful for your company.
A well-organized performance data warehouse will help your company move in any direction you wish. And by clearly defining your data management strategy, you won’t waste any space on superfluous data and will be better able to track trends and determine future data goals.
But companies have to be realistic about what they can achieve. Data aggregates result in millions of pieces of data that must be stored. If you overstep your memory capacity, there are only two ways out — delete valuable data or spend money to increase your memory.
In this way, data management is a plan within a plan: companies not only must determine the source of their data and an aggregating period, but which among competing granularities will be the most lucrative. As data collecting periods occur over months and years, any time lost to an inefficient strategy is hard to recover.
To fully explore what you can achieve with performance data management, try TeamQuest CMIS. With TeamQuest, you can customize your data collection and management strategy to suit your long-term business goals.
We can then filter that data through our sophisticated analytics to determine not only avoidable roadblocks, but the best ways to mitigate risk. There is never a need to passively observe your data — take a proactive approach and optimize your management systems for future growth and agility.
(Main image credit: KamiPhuc/flickr)