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:
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.
Contact Us Today
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
A Winning Base for Successful Digital Transformations When it comes to developing a successful digital strategy, it is not just corporations planning to maximize the benefits of data assets and technology-focused initiatives. The Government of Western Australia recently unveiled four key priorities for digital reform in its new Digital Strategy for 2021-2025.Explore
Engage Your Workforce with a Modern Employee Intranet Solution The employee intranet has changed significantly since it was first introduced in the early 1990s. What started as HTML-based static portals have now evolved into intuitive communication tools complete with search engines, user profiles, blogs, event planners, and more. Today, many organizations are taking a second look at employee intranets to bridge gaps between teams, build company culture, centralize information, increase productivity, and improve workflow.Explore
Adopting emerging cloud technologies, consolidating resources, and improving processes is the key. “IT no longer just supports corporate operations as it traditionally has but is fully participating in business value delivery. Not only does this shift IT from a back-office role to the front of business, but it also changes the source of funding from an overhead expense that is maintained, monitored, and sometimes cut, to the thing that drives revenue,” said John-David Lovelock, research vice president at Gartner.Explore
Deliver Powerful Insights Instantaneously with Federated Queries - No Matter Where Your Data Resides The concept of federated queries isn’t new. Facebook PrestoDB popularized the idea of distributed structured query language (SQL) query engines in 2013. Over the years, AWS, Google, Microsoft, and many others in the industry have accelerated the adoption of a distributed query engine model within their products. For example, AWS developed Amazon Athena on top of the Presto code base, while Google’s BigQuery is based on Cloud SQL.Explore
What is Unstructured Data? Almost 80% of the data that enterprises and organizations collect is unstructured - data without a set record format or structure. Unstructured data includes data such as emails, web pages, PDFs, documents, customer feedback, in-app reviews, social media, video files, audio files, and images.Explore