It’s high time to change the proverb ‘Survival of the fittest’ to ‘Survival of the smartest’. The exponentially growing global economy, fast-paced business world, and ultra-modern technological advancements are compelling everyone from a small company to big corporations to increase their client base and grow the business more.
Big data science and analytics have changed the course of market strategies and paved altogether new paths for the growth and profit of the companies. We have entered the digital age in this decade and the big data analysis is the latest digital technology that has accomplished even unbelievable tasks in real-time. By the end of 2020, the big data volume is going to reach 44 trillion gigabytes, breaking down all the previous trends and setting a new business world.
Coexistence of Two Systems
The leveraging of machine learning and traditional algorithms to analyze the Big data for any organization can solve problems in multiple verticals and forecast the business future with greater speed and reliability. Data analytics has been in the Business Intelligence space for quite a long time providing ‘Point solutions’ for specific problems in any business.
For example, Customer churn forecasting, Repayment risk calculation, Customer default propensity, Price points optimization for promotions etc. have been some prominent point solutions across sectors like Insurance, Telecom, FMCG, Retail, Banking and financial services. While the traditional ‘Causative model’ solutions by business analytics providers help in explaining the underlying explanations of a business problem and any corrective measures for the same, it does not often provide a real time systemic approach to the same. The big data analytics does not only develop a high speed reliable solution but also organizes a variety of structured and semi structured sources of company and external data for multiple systemic uses.
Big data analysis originated from data science and it encompasses mathematics, statistics, and many other scientific tools for the analysis of ever-increasing data. With the help of AI applications and machine learning, predictive analysis is performed that brings results categorized into various domains catering to requirements of different business verticals. These accurate predictions help in accentuating the business growth very effectively.