Over the past several years, it has been well documented that big data -- and more specifically, big data analytics -- has been a struggle for IT operations. The analytics results for many have simply fallen short of expectations. Because of this, many IT departments set out to uncover the root cause of analytics failures. But what they didn't realize is that the problem may have been the IT department itself.
Early adopters of big data endeavors initially placed the blame for poor analytics results on the big data tools. The first explanation was that the databases used to store and sort collected inputs were more complex to setup and maintain than initially expected. Next, the blame shifted to the analytics tools and platforms, with many -- including Gartner Research -- claiming they weren’t quite ready for primetime. Even more commonly, the blame shifted to business leaders with the claim that they simply weren’t asking the right questions that big data could answer.
In many ways, the issues investigated indeed were problematic. Yet they ultimately may not have been the true root cause. In the past few years, most the technical issues involved with data collection and analytics intelligence have been addressed. Additionally, business leaders are asking better questions, questions that big data analytics should be able to provide answers to. Yet, even after all these advancements, many organizations are still struggling to find the analytics pot of gold at the end of the rainbow.
Ultimately, this has led some IT departments to do some serious soul-searching. By taking an external view and looking inwardly on the big-data attempts thus far, many are concluding that the field of data analytics is a unique computer science skillset that they simply do not possess in-house. Even if they do have the right people in the data analytics roles, they risk losing key internal staff that can cripple any big data efforts.
Let’s look at reality. The demand for IT professionals with big data expertise is far exceeding supply. That means it’s difficult to find and keep anyone with the proper skillset. And if your plan is to train current employees, be ready for a long and expensive road to get them up to speed. And even if you do properly train in-house staff, the lure of staff to move on to more lucrative prospects within other organizations will be a serious challenge to extinguish.
Like so many highly technical niche verticals before this one, many IT decision makers are realizing that the real key to big data success is to simply outsource parts of it to a third-party company that specializes in the specific analytics the organization requires. In fact, Hexa Research, Inc just released projections that between 2016 and 2024, the demand for outsourced data analytics services is expected to increase 30%. So, whether you’re seeking prescriptive, predictive, or descriptive analytics, there’s an analytics service provider out there that almost certainly have the right data science skills to meet your needs.
Businesses realize that big data is going to be key part of staying competitive in today’s new digital frontier. Accurate analytics reporting can point businesses into new directions and markets that have proven to be lucrative. But speed to market is often critical. That’s why all the pieces in the complex big data puzzle need to be perfectly put into place. And despite the right collection methods, tools, policies and expectations, finding the right analytics professionals is one piece that isn’t working within many enterprises. The amount of effort to find and maintain data scientists in-house is taking the focus off what’s truly important – accurate business intelligence.