In any organization or IT environment there is no shortage of data being created. It comes from discovery, manual entry, external research and pretty much everything in between. The volume at which data is generated is overwhelming.
Buried in the data is immensely valuable information to your organizations ability to improve process efficiency, direct product marketing or implement effective resource allocations for more profitable products and services. The challenge is in understanding and uncovering those pieces of data that could be your organizations’ secret weapon to growth and success.
In order to make sense of this data, individuals are faced with multiple discovery tools, each focused on its discrete domain that slightly overlaps with another. On top of this, there is often an assortment of manually created and maintained sources with more disparate data. This leaves the individuals with the challenge of piecing the various sources together manually in spreadsheets and locally managed databases to try and understand what is going on.
One of the biggest challenges with this is that the overlaps across data sources are rarely clean or neat. They generally require manipulation which takes time and effort, both of which are at a premium these days in every organization. Ideally, the manipulation is just the truncation of a value but in most cases, requires a second or even third tier assessment to ensure that the records from the different data sources are in fact referring to the same device or item.
Add to this challenge the massive volumes of data that are being generated on a regular basis with no indication of what may have just changed.
Consider the scenario faced daily where there is a need to cross reference multiple sources several times per day to make decisions about incidents, changes or problems encountered in the IT environment. Another example would be the business owner trying to understand how they should change their IT investments but can’t comfortably use the data available to make informed decisions. This is an unsustainable model.
In this abundance of data is incredibly valuable information that holds secrets to the success or growth of your organization. The correlation of data across sources might offer insight into the resource restrictions that support a very high margin product line. It might indicate that a certain service is highly over-architected and hence devices are sitting idle the majority of the time, burning through licenses and leases. There is lots of critical information buried in the data that simply needs to be exposed and acted on.
Expecting individuals to aggregate and manipulate the data they need on a daily basis is unrealistic, but not everyone has accepted it. Instead we need to leverage tools that can aggregate the raw data and coalesce it with the business perspective to provide enhanced value to decision makers. This needs to be done on a regular basis depending on how quickly the sources change. It can’t be done just once, or every now and again when someone gets around to it.
The added benefits of automating are the individuals who used to do this manually can now focus their energies on the real work of making informed decisions and supporting their business partners.
The volume of data that individuals are dealing with is not going to get smaller. It will only continue to grow. Whether it’s because of the new discovery technologies, automation capabilities or the integration of IoT device management systems, the volumes won’t shrink.
In parallel to the growth in volume is the increasing demand from the business to make more accurate and informed decisions at a faster pace, neither of which is feasible manually. And hidden in the masses of data are the key elements that your business leaders are looking for to make vital business decisions.
451 Research published the findings from their study into how organizations are managing the quality of the data being produced by their IT systems in their “The State of Enterprise Data Quality 2016” report that you can download here.