Data analytics is the discipline of examining raw data to make conclusions about that set of information. All the processes and techniques used in data analytics can be automated into algorithms that work on raw data. Businesses can use it to optimize their performance.
The type of data analytics best suited for a company is decided by its development stage and what type of brand and it wishes to implement. Businesses are using sophisticated data analytics solutions with AI capabilities to make advantageous decisions and help discern opportunities and market trends.
Types of data analytics
There are four main types of data analytics:
- Predictive data analytics: It is used to identify various trends, causation, and correlations. It can be further classified as statistical and predictive modeling, but the two are closely associated with each other.
- Prescriptive data analytics: It is used to predict outcomes and necessary subsequent actions by combining the features of big data and AI. They can be again classified as random testing and optimization.
- Diagnostic data analytics: It analyses the data from the past to identify the cause of an event by using techniques like data mining, data discovery, and drill down. It is further divided into two categories, namely query and drill-downs, and discover and alerts.
- Descriptive data analytics: It is the foundation of reporting, addressing questions like “how many”, “where”, “when”, and “what”. They can also be subdivided into two categories, namely, canned reports and ad hoc reporting.
Data analytics in education
When data analytics is used for educational activities, it is called “”. Different educational institutions worldwide use these tools for analyzing various data pertaining to school student verification and teacher verification. This includes studying factors like test scores, teacher performances, and graduation rates. The various pieces of information collected about the schools can be made into a data set, creating big data that can be used to the advantage of the teacher and the school.
The volume of big data can be significantly large, which calls for the need for a data analytics system to help efficiently process the information and make strategic decisions based on it. Teachers and educators can utilize data analytics to document and inspect data sets like:
- Student data: Information about the students like age, gender, and ethnicity, the nature of the course, whether part-time or full-time, whether taking online or offline classes, and the number of subjects taken can be recorded.
- Course data: Information on various courses, like the number of students enrolled, the number of students passing a particular course, and the rate of completion of courses, can be recorded.
- Instructor data: Information about the teacher like age, gender, and ethnicity, number of classes instructed, productivity, and salary can be recorded.
- Facility data: Information on the school or university, like resource allocation and utilization is recorded.
Benefits of data analytics
Using data analytics in the education sector, specifically for teacher verification, has a lot of advantages.
- Data analytics greatly improves decision-making capabilities since they use valid data and statistics to arrive at a decision rather than going by blind faith. Improved decision-making will create more successful outcomes. This will allow the educators to understand the needs of the students and act accordingly, thereby improving student results and pass percentage.
- Using data analytics will help to store the collected data in a neat and organized fashion. The main advantage of this is that it will be easier to access data as and when required without wasting much time. The time saved can be used for other productive activities.
- Since all the information is stored and organized perfectly, it can be made available to future prospective candidates in the form of fact books elucidating the various positive aspects of the institution with the help of statistics. This will be beneficial for both the students and the teachers.
- Communication and collaboration between different departments can be improved using these techniques. Interdepartmental data sharing can help increase productivity and transparency. It also helps teachers to avoid performing redundant tasks, thereby saving time.
How to make the best use of data analytics
The decisions made using definitely improve the outcomes, but to ensure the optimum operation, it is necessary to follow certain important recommendations:
- Data should be collected accurately and in a timely fashion. Real-time collection of data will facilitate intervention and differentiation. Similarly, regular assessment of data will also help to implement corrective measures at the appropriate time and will help the teachers to have a better understanding of learning gaps.
- Professional training should be given to managers and teachers who are involved in data collection and assessment to avoid human errors. Collaboration between data collectors should be encouraged to help learn from each other.
- Collected data should be represented in forms that can be easily understood, like graphs, photographs, and summaries.
Data analytics assists teachers and institutions in performing their teacher verification and student verification duties more effectively, as well as achieving greater success.