The internet came into widespread use about two decades ago, and since then, there has been a constant churning of data. So much so, that today, almost 2.5 quintillion bytes of data are generated each day. This information spread across a wide array of topics, when utilized efficiently, can give businesses critical insights into operation. Big data, which focuses on using data to deliver insights, has been touted as being the beacon of changing business operation. It can give business analysts accurate predictions about the outcome of their particular business models, and can even help them decide which strategies would reap the most benefits.
For instance, a team of researchers at MIT used location data from users’ mobile phones to forecast the number of sales that would be registered at Macy’s on the Black Friday sale. This estimate was arrived at by solely designing big data models, even before the transactions had begun taking place. When it comes to business analysts, this significant effect that big data has on businesses only further necessitates their need of getting a big data certification. However, it comes with its gamut of opportunities and challenges, some of which are discussed below:
Challenges with Big Data
While big data offers many opportunities, the scope of big data is still underutilized due to the challenges posed by it:
Big data inherently deal with vast quantities of data; hence, it becomes difficult to incorporate all the concerned data sets in the initial stages of the project lifecycle. Sometimes, many key metrics that are to be analyzed get discovered later on in the project, thus making scalability even more important. However, since big data projects are extremely extensive in nature, the ability to scale the project up and down becomes extremely difficult. This poses a problem in business analytics as continually pausing a project to add datasets layer cuts into data analysis. While the extent of this challenge posed by big data varies according to the nature of the project, scaling would become faster if the projects were deployed on cloud, instead of on-premise solutions.
2. Lack of Predictability:
While one of the core objectives of big data and business analytics revolves around making relevant business forecasts, the very process of working with a big data project is highly unpredictable. Considering the massive amount of data involved, business analysts often miscalculate the time in which the big data project could grow and evolve. Further, big data loads often tend to come in short intervals, thus making it difficult for analysts to determine where resources are to be allocated accurately.
3. Data Quality:
Data quality is yet another challenge faced by business analysts in their big data projects. Not only is sifting through valuable data a time-consuming process but storing the organizational data in its original form further compounds the problem. As a matter of fact, storing redundant data costs as much as $600 million to enterprises in the United States. Redundant data can be reduced by identifying some of its most common sources, i.e., duplicate data, user input errors, and incorrect data linking. If left unidentified, redundant data has to be meticulously maintained and cleaned by business analysts.
Big Data Opportunities
While the number of challenges associated with big data can be overwhelming, it comes with its share of lucrative opportunities. Big data analysts who can identify these opportunities in time and follow the best course of action can gain a significant competitive advantage from their peers:
1. Extensive Insights
Big data deals with millions of data trails left behind by people through their browsing history, GPS data, sensors and gadgets, social media, and so on. This data also grows every day, at the rate of 50 percent every year, according to a report by IDC. Business analysts who can capture and process this data to make extensive consumer insights will significantly benefit their organizations, thus giving them an edge over their peers. The more insights a business has on its consumer preferences, the more proactively it can respond to their needs. Business analysts can use big data to perfectly outline these preferences, thus empowering businesses to make better decisions.
2. Increased Demand
The advent of big data is poised to redefine the area of responsibilities expected out of business analysts, wherein they would be required to make sense of large bunches of raw data. New opportunities will open up as they would be able to provide the exact stories behind facts, figures, and numbers generated from fresh data sets. This surge of big data will create a higher demand for business analysts as they would be qualified to enhance the business by defining specific data requirements. Business analysts are also tasked with making sure that reporting needs are met and ensuring that the relationships between various data elements are defined.
3. Speed and Efficiency
One of the most lucrative benefits brought about by big data in business analytics is the increased speed and efficiency in all its process. While business analysts earlier had to go through the lengthy process of information gathering and running analytical models before deriving suggestions; big data allows them to identify relevant insights to suggest immediate business decisions directly. This ability to deliver faster and more updated insights gives business analysts the agility that they wouldn’t have had otherwise.
The variable nature of big data poses its own sets of opportunities and challenges in a business analyst’s career. However, when measured, the benefits provided by big data far outweigh the challenges posed by it. Big data is still emerging as a niche, and an extensively data-driven technology would define the coming years. So, keeping themselves at the top of the technology curve by learning more about big data and investing in a big data certification would give any business analyst a boost to their career.