Big Data is a powerful tool for gaining important and useful insights, but many companies face challenges or outright problems while implementing Big Data technology.
In this article, we are going to take look at some of the varied challenges you will face while implementing Big Data.
Technology of Big Data is continuously evolving. The tools and analytics techniques that are used now to derive useful insights might become obsolete within a couple years. Moreover with emergence of the Internet of Things (IoT), we are seeing an ever-increasing number of devices getting interconnected into a complex web. Most of these devices capture and report several types of signal and logging data, which is then provided to Big Data analytics tools to gain insights. Thus, while implementing Big Data you must take into consideration its evolving architecture and plan your company’s hardware requirements and business intelligence platforms accordingly.
Big Data analytics can give you critical insights only when you choose right data sets to analyze. This is why cleaning up is an important factor to consider for ensuring that incomplete, inaccurate, and duplicate data is removed. This should be the first step of any Big Data project. Your data analyst team must understand this and initiate data clean up for gaining tangible results from such a vast amount of data.
Researchers believe that the amount of data under management in organizations has grown five times over the past four years. Yet, many companies still lack the proper knowledge and tools to manage this data. If enterprises want to harness the power of Big Data insights, they will first have to find ways to unravel it. This means that companies should be able to sort through the data, and decide what is important, and either archiving or getting rid of the rest.
Business and Big Data Alignment
Business goals and Big Data strategy should be closely aligned before the company makes any IT investments. You must be able to answer whether or not you company will gain any competitive advantage through the use of Big Data analytics. And whether is it really required to invest in Big Data and analytics. With all the hype around Big Data, it’s little wonder that organizations are now getting caught up by the idea of having their own Big Data initiatives. But even though this idea sounds promising, the reality is that over half of all Big Data projects never reach fruition. Clearly there is a major disparity between the idea of Big Data and its successful execution. Thus, companies should have clarity about its requirements and goals.
The foundational technology that supports every Big Data initiative is the Hadoop analytics platform. There is a lot of hype surrounding Hadoop and its ecosystem of tools. Organizations believe that Hadoop has the ability to handle massive volumes of structured and unstructured data and bring out hidden insights that an organization can use to create competitive advantage. But, what they do not know is that this software is not only hard to manage, but it is relatively new too, so it can produce real challenge for data professionals that aren’t familiar with it. Moreover, Hadoop often requires extensive internal resources to maintain. Thus, while implementing Hadoop, businesses should be well aware of this technology and its requirements.
These are some of the challenges of Big Data, but needless to say its benefits are abundant. From discovering revenue streams and insights to uncovering untapped areas of efficiencies, there are several other advantages that you can gain from Big Data. Even though you might face some challenges while implementing Big Data, you should focus on choosing the right team and selecting the best software for your data needs. This will help you in the long run and ease out your difficulties.