In a rapidly-digitalizing business environment, big data and analytics have emerged as vital cogs in the machinery of the global economy. It is, therefore, critical for 21st century enterprises to efficiently manage the data explosion and optimize it. However, the task is gargantuan and enterprises face quite a few challenges in storing, managing, utilizing, and analyzing this data deluge even as it is growing by almost 60% year-on-year. As a result, it is a crucial prerogative for organizations to address and resolve the various big data and analytics challenges.
Let us take a look at five of the more significant big data challenges faced by enterprises.
1. Using Big Data Meaningfully
The core idea behind the various innovations in the field of big data and analytics is deriving meaningful insights and making it available across an organization. However, so far, organizations are struggling to get the best out of unstructured data, leaving room for improvement. Furthermore, big data and its analysis is still limited to only a few people within organizations and not everyone has access to them in order to action them in their work.
2. Too Many Big Data Technologies to Choose from
Being spoilt for choice in an evolving tech landscape is ideally a good thing. But, with companies still coming to terms with the various big data innovations, a plethora of technologies to choose from seldom helps. A flawed choice can result in a long-term issue for an organization. Understanding the exact requirements of an enterprise and choosing the right technologies for them is key to seamless big data management.
3. Data Security Loopholes
With big data and analytics tech developing on a daily basis, it is fairly difficult to keep data breaches from happening. The adoption of big data is complex and cumbersome, with very little focus on data security, at least in the initial stages. As a result, the data is left vulnerable to cyberattacks and digital malpractices in the interim.
4. Scaling Data Analysis
As it is, adoption of big data and analytics is complex and costly. Yet, progressive, enterprise-wide upscaling poses further challenges. Introduction of newer storing and processing capacities require seamless integration, and scaling the process effectively while not overshooting the budget gives enterprises some serious headaches.
5. Shortage of Skilled Professionals
Big data analysis innovations and upgrades are flooding the market. But, human skills are not being able to keep pace with them. As a result, for organizations taking to the big data and analytics wave, one major challenge is finding and recruiting skilled personnel for the task. As of now, there remains a glaring skill gap, compromising big data initiatives to a large extent.