Dr. Pratima has been associated with Symbiosis for over a decade now, prior to which she held key positions at Hero Corporate Services and AC Neilson, and was even awarded a honorary Doctorate from the Symbiosis International University.

Educational institutes generate large amounts of raw and diverse data pertaining to students, faculty, curriculum and other academic activities on a regular basis. This data if leveraged intelligently, can provide some useful insights and uncover hid-den patterns or reliable correlations to improve and optimize the learning process. Data analysis can enable educational institutes to convert plain numbers and facts into meaningful information to draw analytical conclusions. Data analysis has gained traction in almost every industry and is transforming the way businesses are conducted. Let's take a look at how data analysis is influencing the higher education system.

Self-Paced Learning & Monitoring Learning Progress
Every student has different learning capabilities and potential. Some are fast or gifted learners and need to move onto the next level quickly. Some are slow learners and need to devote more time to studies. Then, there are some students who have to balance their studies along with personal or professional commitments.

Data analysis can enable educational institutes to design curriculum and lesson styles keeping the learning curve of students in mind. They can also keep a close tab on the learning progress of students, understand the factors that affect their performance, and make targeted interventions to improve their academic results and prevent/reduce dropouts.

Self-Curated & Co-Created Content According to Learner Interests & Learning Styles
Traditionally, curriculum and course structure is the sole responsibility of academia. In most cases, the institute or faculty fail to take the interests and learning styles of students into consideration and end-up designing a `one size fits all' curriculum. However, data analysis can help identify the interests and core strengths/weaknesses of students based on their previous academic scores ­ subject/topic-wise. Data analysis can also be instrumental in discovering dominant learning styles of students ­ verbal, visual, aural, logical, or any other means. Based on such kind of data,

educational institutes can seek active participation from students to either self-curate or co-create content. This will not only customize learning for students and align it to their interests, but also teach them to take its ownership.

Examination Type & Time Management
Short answers, descriptive answers, multiple choice, computational, essay-style, open book, oral and practical ­ there are different types of exam questions and patterns. Often, students are unable to answer the questions as per the prescribed marking scheme or time limit, which in turn results in poor scores. With the help of data analysis, faculty can generate structured information on how much time each student has taken to answer each question and guide students on time management techniques. The difficulty levels can also be set as per the learning curve of the individual.

Data-backed decisions can eliminate the risk of errors and biases, as they are based on logic, facts and statistical reasoning

Any Time, Any Place Learning in Customized Chunks
These days, a number of educational institutes have commenced online/e-learning courses to offer benefits of flexibility of learning to students in terms of time and location. Now, since these courses are disseminated via computers and mobile devices in different instructional formats ranging from video tutorials and live interactive sessions to blogs and social networking sites, data is generated in huge volumes. It becomes really challenging to process and organize the learning outcomes of students and optimize the efficiency of their learning.

Data analysis can streamline all bits of information in real-time. It enables to understand learners' demographic profile, educational needs, learning styles, monitor their performance, and give them instantaneous results & feed-back on improvement areas. In fact, data analysis can also predict the future performance of the learners and customize the content/learning style to boost the learning outcomes.

Data-Driven Decision Making
The decisions made by educational institutes can have a direct impact on their reputation and learning of students. However, most decisions are based on experience and instincts. There is a high possibility that these decisions can go wrong and prove detrimental to the institute. On the contrary, data-backed decisions can eliminate the risk of errors and biases, as they are based on logic, facts and statistical reasoning. Educational institutes can leverage data analysis to make informed decisions about policies, practices, curriculum, staff recruitment, admissions, placements and every other aspect of education.

Focus More on Core Tasks & Less on Administrative Activities
Educational institutes spend a chunk of their time in administrative activities such as developing curriculum, managing class & exam schedules, maintaining attendance records of students & staff, evaluating test papers, handling admissions & placements, communicating with different stakeholders, meeting regulatory compliances, and much more. While computers and digital tools have eased-out the administrative burden significantly, it is a tedious task when it comes to pulling-out records or preparing explicit data-based reports.

Data analysis can automate most of the administrative activities and generate reliable and accurate information. This leaves more time for the faculty and staff to focus on the development of students and best programme improvements. Data analysis is still in the infancy stage in the education sector. But given its potential benefits, it wouldn't be long before it takes the centre stage in transforming the educational system.