Artificial intelligence and machine learning is everywhere, from apps consumers use every day, to business applications that enable businesses to make better decisions that drive revenue. In fact, it is rapidly transforming the ways that industries like healthcare, banking, energy and retail operate.
One industry that could benefit massively from this technology is education. With it, for example, institutions could provide a personalized learning experience in which every student would enjoy a completely unique educational approach. Technologies like chatbots - that ensure a further personalized experience for students - can also be implemented. But the big benefits lie in research facilities that rely on data being available constantly in the most cost-effective and optimized way.
This does, however, pose certain challenges, not the least of which is data management for higher education institutions.
Big Data in Education
Higher education institutions like colleges and universities have, for years, been collecting large amounts of data about their students, programs and facilities. In addition, researchers have been gathering massive amounts of data for their research projects. Until the advent of ‘big data,’ these institutions could not use that data effectively to transform higher education and research, and had to rely on traditional methods of sourcing, collating and analyzing data.
With the emergence of ‘big data,’ these institutions are imagined as smarter universities that offer a multitude of benefits that go beyond just learning. Some of the benefits effective data management offers are:
- It helps higher education institutions answer the tough questions. By looking at their existing data, institutions can be in the best position to strategize about their future and the challenges facing the education field.
- It is accessible. There is no more searching for files in endless filing cabinets or scouring departmental PCs for a vital piece of information. With the right technological infrastructure to capture, store and manage data, it is much easier to find the information in an instant—often through something as simple as a web browser. Also, data analytics makes it possible to create a more collaborative environment with all the information needed in one central location. So, lecturers get the information on students they need, administration can make decisions faster and researchers can do more in less time.
- It saves money. When it comes to higher education, precise resource allocation is crucial, and data is the key to efficiency. This means classes can be optimized based on the number of students, classroom space and the lecturer’s time. From an infrastructure perspective, cloud-based systems can cut data storage costs and ease the load of the IT department. Not only this, but it can also automate a lot of the tedious work in the administration and makes accessing data easier which saves money over time.
- It is fast. With all the institution’s information available in one centralized location, they will save a lot of time in finding the data they need. The data is also available in real time, so institutions are able to make decisions quicker than ever before and do not necessarily have to rely on historical data only. Likewise, researchers do not have to wait for days or weeks for data or resources as it is available in an instant.
- It helps institutions adapt. The data will help institutions to identify new trends, and as they are identified, institutions can develop new classes or teaching strategies that adapt to these trends. Here, institutions can shift some learning to online classes or implement more personalized ways of learning to improve their students’ learning.
The common thread through all these benefits is that the data should be available instantly. This, in turn, relies on the right data infrastructure to optimize an institution's data management. And this poses some challenges, like cost optimization and data availability.
Meeting the Data Management Challenges in Higher Education
When it comes to managing the costs relating to data management for higher education, institutions have two options. The first is to build a data management solution in-house, purchasing the needed hardware, storage and software. The second is moving to a cloud-based infrastructure where institutions pay based on their consumption or their usage. This means they do not have to make large capital investments to establish a data management infrastructure and data resources for their environment.
Institutions can further optimize their infrastructure costs by using an automated data management platform like TimeXtender to help them implement and operate data lakes, data warehouses and data marts. Once established, lecturers, researchers, and administration staff can get access to the data via a simple self-service portal.
By doing this, institutions ensure that:
- They have a robust solution that performs well, and all their data is available at all times for analytics or artificial intelligence implementations.
- Their data infrastructure is fully scalable and ready to adapt to new technologies.
- Their data is secure and in compliance with regulations like the GDPR and other privacy laws.
This also solves the data retention challenge in data management. By implementing a modern data infrastructure through a data lake and/or data warehouse, institutions can ensure they meet the data retention requirements related to grant-funded research. And, even if they do not, they will have the necessary data retention policy in place that determines how frequently users and applications will access data in the cloud, which in turn ensures that the data is secure.
With the impact data is having on educational institutions, infrastructure is incredibly important. In other words, infrastructure optimization should be on the top of any institution’s list when they look at data management and are looking to make a cost-effective transition to a cloud environment.
TimeXtender offers all the tools necessary for an organization to build a data estate for analytics in the shortest possible timeframe. It is specifically designed for the Microsoft Azure ecosystem, and it automates the process of getting data from source systems into Microsoft data platforms like SQL Server, Azure SQL Database, Azure Data Lake and Azure Data Warehouse.
An added benefit is that it offers a no-code way of building the data infrastructure. So, it accelerates, simplifies and automates data modeling, integration, extraction, cleansing, loading and documentation using low-code development patterns and functionality. This means it is significantly easier and more cost-effective than hand crafting data warehouses with large, highly skilled teams and months of development.
If you need more information on TimeXtender’s data management platform for higher education, feel free to contact us or visit our website for more information