According to a recent article published in Times Ascent, Amol Mahamuni, the Program Director of Indian Software Lab quoted “Business today is facing new challenge with respect to data volume, velocity and variety." The "velocity" of data is becoming a new challenge for the IT sector.
The following will shed light on why big data analysis is the most ‘in’ thing in the Business sector, and why India needs more of Big Data Hadoop specialists.
Big Data Hadoop Analysts are required to get insights more than just keeping a system of records. Volume of data has been increasing exponentially. Data comes from a variety of data sources such as text, sensor data, audio, video, click streams, log files, and more, out of which 75% of data is unstructured. Everyday new insights are found by analyzing and monitoring hundreds of data.
Read below how Ascent Transformation Series’ third panel delved into the need for adopting big data analysis to attain bigger business outcomes.
How Big Data Hadoop is used today and Big data’s impact on the future?
Telecommunication business derives information by understanding the call pattern analysis
A variety of data is collected through hospital information system to prepare personalized medicine
Retail business can benefit from social sentiments and click stream analytics and simultaneously optimize their supply chain
Used in Stock market to analyst stock market sentiments
Big data attributes in high revenues for any business since it is the art of targeting consumers with the right offer at the right time
Also, significantly gaining prominence in predicting election outcomes and econometric models.Â
Learn how big data will affect you 2015
What Big Data Analysts are required to do?
They should have technical skills like machine learning and mathematical modeling, to skills like data management. All in all, a business analyst has cross-functional skills that he needs to exploit. Big data Hadoop training has become omnipresent, which is why it is worth noticing how significantly it has been helping to drive revenues in e-commerce, social media, online retail and ads.
Demand forecasting and inventory management of large number of stock keeping units
Supply chain management
Collaborative planning and design.
Patient care using real-time data
Analysis of correlation between treatment and outcome
Target segment Identification
Customer Attrition Management
Banking, Finance and Insurance:
Real-time trading in global markets
Adherence to compliance and country regulations
Real-time fraud detection
Cross-selling and Up selling