Students’ Corner
Three Pillars of Analytics and their Need in Post-Covid Era
Ms. Pragya Ram Nanwani Student - MBA06 IIM Amritsar
“The last ten years of IT have been about changing the way people work. The next ten years of IT will be about transforming your business.”?Aaron Levie, CEO of Box.
and performant analytics models, reliable and fit-forpurpose infrastructure is required.
Businesses have been transforming themselves for a long time, but, Coronavirus pandemic has accelerated the adoption of digital transformation like nothing before.To thrive in our new virtual business world, companies have been forced to ramp up their digital strategy quickly. Those that were unable to pivot and reset their business plan on time did not survive.
According to Gartner's 2019 CIO Agenda survey, firms that used AI increased from 4% to 14% between 2018 and 2019. Companies must look beyond the traditional use of CPU power to support their AI and Machine Learning applications using Graphics Processing Units as AI continues to grow. This will motivate them to design, train, and retrain their analytical models and run them more rapidly, resulting in better customer products and services.
In a post-covid era, businesses that progress digitally will engage more directly with customers, accelerate innovation, and hence demand a larger share of profit in their industries. Every business has the potential to become a digital one. Today's digitally changed businesses have an advantage, and only digital businesses will prosper in the future. The goal always remained to create a data-driven organization. The times, however, have changed. Data must now guide businesses to survive in the unpredictable post-COVID-19 environment. The ability to quickly adapt and alter the business plan with personnel, goods, and processes based on actions, whether on the global market or within the company, is more apparent today. This means that advanced data analytics is essential for running realtime business processes. Beyond data-driven, the goal now is to use advanced data analytics to drive real-time business planning. Data and business analysts must focus on strengthening the three pillars of data analytics: speed, performance, and agility, to alleviate dissatisfaction and provide a better analytics solution and experience for the organization. The foundation for enabling these pillars is the entire data architecture backed by a sound data strategy. To handle increasing data volumes and accommodate more advanced A-GRAM | 06
Speed
GPUs enable businesses to massively parallelize activities to assist the training of analytical solutions and/or inferencing, allowing them to finish numerous epochs in a quicker timescale and fine-tune the model. Furthermore, deploying GPUs in the cloud enables businesses to execute a variety of AI/ML workloads with the flexibility required for a cost-effective, scalable, and secure AI solution. Whether a healthcare provider provides more accurate, faster diagnoses or a retailer provides more tailored customer experiences;more businesses are using AI. According to a 2018 Forrester survey of data and analytics decision-makers, 53% of businesses employ AI.
Performance Semi-structured and unstructured data are significantly more difficult to evaluate than structured data, yet they are far more common in businesses. The proliferation of IoT and social media content, according to IDC, will result in 80 percent of global data being unstructured by 2025. Organizations need to bring a wide range of data together in a 360° view that gives deeper, more accurate, and precise analytics insights to stay competitive. It's not always easy to tell what data is structured and what
