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Importance of Data Analytics, Data Visualization and Automation in 21st Century Education

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Posted on Jan 07, 2021
by Dev Kumbhare ( Sr. Manager Business Development)

Importance of Data Analytics, Data Visualization and Automation in 21st Century Education

In today’s modern education system, technology is playing a vital role in providing timely access to the right data and reports that can help generate trusted knowledge and insights and transform programs, curriculums, student outcomes and more – in ways that deliver desired results faster. In this fast-paced dynamic environment the students and teachers need quick answers or resolutions to their many questions. Educational Institutes have to operate with limited IT manpower for both developing and supporting IT infrastructure. Schools, universities, colleges and educational bodies hold very large amounts of data related to curriculum, students and faculty which has prompted them to expand the use of data visualization, analytics and automation tools to turn vast amounts of data into data-informed insights. Let’s see some examples of how these tools are creating an impact and driving the Education industry:

1. Data Analytics:

  • Using data mining, statistical analysis, forecasting, text analytics, and optimization and simulation, institutions can access student’s progress during each semester which can allow advisers to intervene promptly with outreach to students who are underperforming. Big data analytics monitors student’s activity such as their favourite subjects, their classroom performance, extracurricular activities, the time they take to finish an exam and many other things within a student’s educational environment.
  • Processing of data-driven systems using Advanced Analytics and AI can help institutions create customized learning experiences according to student’s learning capability and preference.
  • Deep analysis of student’s progress reports and academic performances can help in understanding areas of interest where he/she can pursue a career.

2. Data Visualization: With the use of data visualization tools like Power BI, Tableau, Qlik or similar, schools, colleges and universities can gain deeper insights about several aspects

  • These include student behaviour, testing results, careers developments of students.
  • Gain reports on usage of resources in the campus/across the university and take necessary steps for optimization of these resources.
  • Gain reports on success rates of courses. Course success rate data is a way to gather the context to know if a specific curriculum is effective or not based on course acceptance/adoption by students.

3. Automation: Automation techniques using tools like Python, R, Uipath etc. can help eliminate paperwork and manual processes prelevant in the institutions.

  • Admission and Enrolment Process – Using automation to assess student’s eligibility criteria, validate information, shortlist candidates to avoid tedious manual processes.
  • Admin & Finance - Automate processes like payroll processing, accounts payable-receivable vendor management.
  • Allotment of classrooms, recreation areas in the campus– Analyze campus & classroom capacities and optimize allocation for each academic term.
  • Chatbots – Chatbots to help automate general queries from students, staff and website visitors like admission schedule, admission process, contact person, course information.

Although Data Analytics, Visualization and Automation allow for very exciting changes in the educational field, implementing transformative software solutions in ways that are widely adopted and deliver expected benefits can be challenging. Technology companies like can help education institutions adopt and implement these technologies towards achieving the most crucial goal of any educational institution which is to offer high-quality education to its students. Aress has the relevant domain along with Machine Learning, AI, Power BI and Tableau certified consultants and developers that helps in successful use case identification, quick proof-of-concept, larger project development and deployments.

Category: Data Analytics, RPA & AI

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