Cloud computing has now become mainstream in the higher education sector. Institutions across the board are deploying different versions of the cloud to minimize capital expenditure, reduce time to market, and boost flexibility and scalability, among other objectives. One emerging area of focus, with regard to cloud implementations, is helping education providers make better and quicker decisions based on data.
While the importance of analytics has traditionally been recognized in education services, its true potential is yet to be harnessed, in spite of institutions owning rich data sets. For a surprisingly long time, ensuring student success and retention were not determined so much by data-driven decisions as much as by factors related to other campus initiatives. The reasons could have been many – the presence of data silos across different departments, the absence of advanced analytics software, or the lack of skilled staff with time and resources to focus on analytics.
While data analytics has now become far more sophisticated and capable of offering predictive insights, it still remains out of reach for many colleges. The high costs involved in setting up the necessary infrastructure and data management practices on-premise represent a significant barrier to adoption. This is where cloud-based analytics solutions provide the best of both worlds –advanced insights at significantly lowercosts.
Apart from the ROI, there are quite a few other reasons why the cloud can facilitate superior analytics for education institutions:
- Analysis of high data volumes from diverse sources: With students and staff interacting with universities through multiple channels, data today originates from diverse sources. Moreover, the high volume of data generated from social media, smart campus initiatives and better student engagement activities require systems that can seamlessly manage these traffic sources, without putting a strain on existing resources. Cloud’s ability to easily scale as needed and manage Big Data can be a key differentiator here.
- Real-time analysis: Cloud analytics can be used to mine real-time data, and offer insights on-the-go for university managers and staff, who can continuously monitor the outcome of various initiatives even as they roll them out.
- Self-service and instant provisioning: Cloud Analytics solutions typically come pre-packaged with data models, reports and advanced tools. Users will also be able to opt for consumable services to extend functionalities through self-service instantaneously, without relying on IT staff for procuring and configuring new tools.
- Data-driven decision making: Cloud can enable education institutions to consolidate their data sources effortlessly and implement better data governance practices. This, in turn, can allow them to use their data better for deriving more timely and relevant insights.
It is no doubt the affordability and advantages of cloud analytics makes it an attractive solution, irrespective of an institution’s size or financial standing. With education providers seeking to track the student lifecycle for better outcomes, effective usage of cloud-based data mining tools can go a long way in helping institutions deliver what their students want.