Big Data: Its Advantage, Challenges and Relevance
With the emergence of the COVID-19 pandemic, our entire world plunged into chaos. As a result of the global epidemic, one-third of the global population were locked down to their homes. The scary situation left everyone only with the internet to cope up with everyday hassles. With outdoor activities limited to almost zero, every text message exchanged, every series binged on Netflix, and even every Esewa payment we did for groceries, produced a huge volume of data. Just imagine how much data has been produced, shared, and consumed in the world in 2020 alone? Well, the answer is over 59 zettabytes of data.
Based on Big Data, HDFC Bank, the largest private sector bank of India, has been able to understand the personal preferences of its customers enabling it to tailor deals appropriately.
With this much data being generated every day, organizations must be able to align their decision-making towards a data-driven approach rather than an emotional or egoistic one. With the advent of social media and digital-based platforms, data has become the new oil as data has been conclusive in analyzing, interpreting and predicting the behaviors of the customers and employees to a greater extent. And, with that said, the outcome of big data analysis is not biased and slanted towards some ideologies and preconceptions which makes the decision efficient and scientific.
With multitude of perks, it brings to the table, Big Data Analytics has been the priority for every organization to scientifically identify the spending pattern of the customers, profile and segment them, product personalization, cross selling and workplace improvements. Numerous global organizations have gained billions of dollars in revenue by incorporating Big Data Analytics as their sole decision-making tool. Take, for instance, Netflix. Netflix has over 100 million subscribers, which implies that a large volume of data is generated every day. They evaluate this data to improve the user experience. Netflix has summited to the prominence of the streaming industry thanks to Big Data. We are given a list of shows which are relevant to our interests after evaluating our past behavior. The method saves Netflix $1 billion a year in customer retention.
Because Big Data is a large chunk of data, it must be preceded by the 5 V's in order for any organization to derive meaningful insights from its analysis. Volume, Variety, Velocity, Variability, and Value are the five V's that any data ought to have prior to actually making a decision.
Not only Netflix, but numerous organizations in both the technology and non-technology industry sectors have used Big Data analytics to fuel efficiency of their operations. Based on Big Data, HDFC Bank, the largest private sector bank of India, has been able to understand the personal preferences of its customers enabling it to tailor deals appropriately. Also, Big Data analytics aid the bank prevent money laundering by discovering unusual and malicious transactions such as money circulating among accounts, single-day large financial transactions, opening multiple accounts in a short period of time and immediate activity in long-dormant accounts.
However, Big Data Analytics has not been straightforward to implement. The significant obstacles that pushback organizations from implementing Big Data Analytics are legal and regulatory challenges, shortages of skilled labor, privacy & security concerns and organizational culture. However, another hindrance to effective Big Data implementation is Big Data itself. Because Big Data is a large chunk of data, it must be preceded by the 5 V's in order for any organization to derive meaningful insights from its analysis. Volume, Variety, Velocity, Variability, and Value are the five V's that any data ought to have prior to actually making a decision. Having followed the Five V's of Big Data, any organization should have a plethora of varieties of valid data generated every day at a high velocity, which ultimately offers value to the organization.
Corporations have widely used a range of platforms to mine and interpret big data. Platforms such as Apache Hadoop, Apache Spark, Cassandra, MongoDB, and Drill have proven to be extremely effective in synchronizing even SMEs with their Big Data aspirations and are readily available. Since enforcing Big Data is not as simple as switching the button on, the entire organization have to go through the process of transformation, that may even disrupt the current culture. However, I believe that the mindset of the Organization's C suite is more significant than platforms and methodologies. To embrace such innovative ideas, leadership must be transformational and dynamic.
Ashok Sherchan, CEO of Prabhu Bank Limited, publicly confirmed at Kantipur Economic Summit 2021 that a lack of technological infrastructure has hamstrung Nepal to enter the age of Digital Economy with no commitments from the private sector to embark on this transformation.
Even while we have seen such marvelous applications of Big Data in foreign soil, whenever it comes to Nepal, our business models have remained traditional. We have seen time and again that the big corporate houses of Nepal have been resistant to change and new technology. The government has yet to enact dynamic laws and regulations that govern organizations in order to implement Big Data morally and ethically without jeopardizing user privacy. Ashok Sherchan, CEO of Prabhu Bank Limited, publicly confirmed at Kantipur Economic Summit 2021 that a lack of technological infrastructure has hamstrung Nepal to enter the age of Digital Economy with no commitments from the private sector to embark on this transformation. At the institutional level, Nepalese Corporate Leaders now must adopt a new perspective on employee education and training in order to brace for existential threat for business posed by the rapid technological innovations and advancement. “To achieve our goal of being the Digital Bank of First Choice, implementation of Big Data is crucial and serves as the cornerstone”, said Kshitij Karki, HR Supervisor at Civil Bank Ltd. He further added that the new recruits were also not equipped with Big Data skill sets, so Civil Bank plans to restructure its entire employee training program by making Technology and Data Analytics training programs mandatory for all employees.
With a slew of issues at the governmental, institutional, and academic levels, implementing Big Data analytics in Nepal will be a tough struggle. That being said, with greater access to eLearning websites and internationally affiliated education institutions, Nepalese workforce may be better equipped to align their decision-making to Big Data Analytics. The array of hope has been further sparked with Tribhuvan University commencing their Data Science School. The new generation of young entrepreneurs must be able to build democratic institutions that appreciate scientific thinking over self-centered and arrogant decision making. Big Data may not only be a decision-making tool for Nepalese institutions, but it may also navigate us towards productivity & efficiency and spur innovation across public and private corporations.
To sum up, making Big Data relevant in our Nepalese business ecosystem is wholly reliant on the mindset of aspiring young business leaders and professionals. So, are you ready to strap in the seatbelts and embark on the voyage towards Big Data Analytics?