Big Data and The Cloud
The era of big data is well and truly upon us, and it’s no longer a question of whether businesses should engage with big data, as it becomes more and more difficult to gain a competitive advantage if you are not engaged with big data. The volume of data being produced is staggering and will only increase in the near future. Technology giant Cisco predicts that the amount of data produced in 2020 will be 50 times what it is today. No wonder then that companies feel overwhelmed and desperately in need solid advice from specialists who understand their business and have their best interests at heart.
QUALITY DATA OVER QUANTITY OF DATA
The volume of data received by an organization is no guarantor of success. In fact, too much data can be damaging. Making sense of the data and applying it in new and interesting ways to serve new markets and changing business models is key.
Effective analysis is the key to data-driven success.. CloudMoyo CEO Manish Kedia explains how ‘the cloud offers the ability to use machine learning effectively, to scale up as much and as quickly as you need, analyze the next best action and then when the analysis is effectively completed, you can just shut it down.”
This approach is a marked change from an ‘on premise’ analytic system which takes time to build and make operational and then, due to the capital outlay, needs to be re-used over and over again.
CloudMoyo is a global cloud leader operating at the critical intersection between its clients, big data and the cloud. The company defines the challenge of an analytics strategy as “relating business goals and use-cases with how analytics will support employees and the business. Analytics is creating differentiation for modern day businesses by giving greater, more actionable insights.” Whether it’s insights into customer base or supply chain issues, where the competition is succeeding and failing, markets, risks and products, strategic use of big data provides valuable insights which can make or break a businesses.
PUTTING BIG DATA TO WORK
One of the most effective examples of big data being deployed effectively is the partnership between CloudMoyo and the Kansas City Southern Railway Company, which is the third oldest Class 1 railroad in North America. The company has been in operation since 1887 and operates in ten central U.S states, as well as the northeastern states of Mexico and into Canada. Needless to say, it’s a massive logistical business.
(Image Source: Shutterstock)
The challenge for CloudMoyo was that public transportation systems deal with movement of large volumes across an even larger geographical spread. Proper trained personnel must be deployed for the efficient and timely movement of goods. Any delay in movement results in huge financial loss to the operator. With over 2 000 staff members, the operator also needs to ensure that crew allocations are done based on their skillset, which ensures increased utilization of assets and lower downtime.
Through its work on this project and in close collaboration with the client, CloudMoyo was able to deliver a next-generation, cloud-native public transportation management system that addresses all the challenges of managing complex transit operations. The system developed “is cost effective and enables quicker time to deployment for the operators thereby leading to quicker ROI and takes advantage of mobility advancements.”
The company also used its considerable experience in a retail context when it was approached by software giant Microsoft to gain data-supported insights into its chain of retail stores (from products to geography to locations) and make informed strategic decisions. In much the same way, pharmaceutical companies employed CloudMoyo to use real world data in order to understand how disease impacts patients and their communities outside of controlled clinical trials.
The key insight with emerging big data is that companies who are proactive are likely to reap the benefits. It’s no longer enough to retro-actively analyze what happened and why. Instead, systems and partnerships need to be put in place which leverage high quality data and interpret the data to make predictions around what is likely to happen next, with concrete evidence to back up the claims.
Article Sponsored by CloudMoyo
By Jeremy Daniel
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