The intelligence arena has become more complex and powerful in recent years, driven by the simultaneous progression of the technologies used to analyze information and the massive increases in global data volumes. While a greater variety of companies are now beginning to embark upon analytics strategies, one can only hope that decision-makers understand the requirements of doing so from a logistical standpoint.
In some ways, the rapid evolution of the tools can quickly lead one to believe that the implementation of one piece of software will yield all of the insights and intelligence necessary to excel in their markets. However, data preparation and a wealth of other front-end components need to be focused upon to get the most out of information and the analytics solutions themselves, and this will be especially critical as the makeup of files transform.
The consumerization impact
TechCrunch recently argued that big data has already become one of the more powerful tools out there to help companies bolster their customer engagement and retention performances. Again, this is partly due to helpful solutions such as managed intelligence and self-service data prep, but is also significantly rooted in the popularity of tracking activities and lifestyles among consumers of all kinds.
According to the news provider, personal health is one of the more prominent applications of wearable use, while those gadgets tend to be the most weighty drivers of new information generation. Now, because of how successful companies like FitBit have become with respect to gaining permissions among users to gather private information, other types of organizations are starting to try to have a similar approach.
The source affirmed that this presents substantial privacy protection questions to analytics users and vendors, especially given the sheer gravity of the potential these strategies come along with. Balance will be critical to make the most out of the data available without hindering customer engagement on account of poor privacy protections and allowances.
This is yet another complex demand of modern big data that might be overlooked when decision-makers are too fixated on the potential financial advantages of deploying advanced analytics strategies and solutions in their own facilities.
"Businesses must adhere to big data best practices."
The right approach
Simply put, businesses will need to ensure that they are adhering to best practices for both the establishment of successful big data strategies and the reduction of risks that accompany these technologies. This is not to say that big data is inherently impossible to secure, but rather that businesses must put a strong focus on maintaining customer privacy at all times.
On the technological end, data preparation and similar processes should always be handled by service providers and professionals who have plenty of experience in these matters, or the solutions they offer on a self-service model. This can help companies to maximize the value of their big data strategies without corrupting their images or hindering their ability to control privacy protection performances, even while gathering larger volumes of information.