The discipline that takes raw data and analyzes it to arrive at meaningful conclusions is called Data Analytics. The discipline can be used to understand customer behavior patterns, current trends and even be used to predict future events. Other applications of data analysis include data mining, data management, presentation of data, and statistical analysis. Looking at how the field can benefit businesses, many sectors, such as the manufacturing, hospitality, and retail industries, are increasingly making use of this discipline to prosper in their businesses. As a result, new graduates and working professionals are enrolling in data analytics programs to improve their career prospects.
The Role of Big Data Analytics in Assessment
Before we understand the role of Big Data Analytics in assessment, it is necessary to understand what is Big Data Analytics. Big Data Analytics refers to real-time data analysis of huge volumes of data using a set of applications and tools. It is used to make informed decisions as well as arrive at the desired outcomes.
Here are some of the popular techniques used to analyze data:
- Regression analysis: To analyze the relationship between dependent variables to determine how modifying one can affect another.
- Cohort analysis: It is used to disintegrate data into several groups. This technique is used to analyze the numeric data to a certain set
- Factor analysis: This technique considers a large set of data and constricts it into a smaller set. This technique is used to discover the trends that do not appear covertly
- Time series analysis: It is used to spot cyclical trends or predict finance-related events. This technique is used to track data during a certain timeline and establish a relation between the value and occurrence of a data point
- Monte Carlo simulations: This technique is used to prevent losses and minimize the chances of risks. Upon incorporating various variables and values, this technique provides greater forecasting abilities of the probabilities of occurrence of various outcomes in comparison to other data analytics techniques.
How Do Assessments Take Place for Data Analytics Programs?
Are grading and assessment the same? Although used interchangeably at times, there is a difference between the terms: assessment and grade. The goal of issuing a grade to a student is to evaluate his learning and how he has performed in a test (for example, the final exam). Assessment goes a further notch beyond grading. Assessment is conducted with the goal of improving one’s learning. It is often conducted during a course. It can be used to understand the student’s learning patterns as well as to detect ways to improve educational practices. Grading can form a part of one’s assessment.
When you register for a data analytics program, you will have quizzes and assignments (many of which are peer-graded) at the end of one or more lessons that will assess your learning and detect whether you are eligible to move to the next level or have some more learning to do yet.
A data analyst is expected to be proficient in Mathematics and have a strong sense of business. Upon examining the data, he should be able to find patterns that will enable him to offer suggestions viable to the business, such as optimizing the existing business offerings or improving certain outcomes. The analysis should be communicated to the stakeholders in concern.
Considering these objectives, data analytics programs are designed with a set of questions that test the learner’s proficiency in Maths and business. Besides these, the tests also assess the learner’s ability to use and classify data in different situations and to solve various problems and his critical thinking ability.
Applications of Data Analytics in Education
There are several advantages of using Big Data visualization in online educational applications:
- Using tools, educational institutions can use the large volumes of data collected to store, organize, gain insights and analyze complex data, and manage it.
- This can be used to analyze student demographic data, right from their age to their scores. Similarly, it can provide important information regarding the course delivery. The data thus obtained can provide information regarding learners’ problems as well as optimization of teaching resources and analyzing course-related information.
- Big Data helps not only to craft individual lessons and lesson plans but also aids in the enhancement of learning by personalizing and reshaping a learner’s experience. Assessing students’ learning using performance indicators helps both teachers and students to gain insights related to performance in real-time right from the first day.
- Data Analytics can be used to supervise the motivation and engagement levels of the learners in the program.
- Since all the data about students, research, and teachers are collected in one place, one can look for the information desired organized in the files and folders. This helps to streamline processes as well as boost efficiency and save time.
Those who have learned the required skillsets from the data analytics program can also apply their skills in the EdTech firms to procure new growth opportunities and increase the revenue of the businesses. The feature of generating revenue and exploring business opportunities is a crucial feature of why data analysis is used in various other industries.
Conclusion
Data is the key in today’s workplace, both for the progress of organizations and individuals. Firms across industries are increasingly relying on data, statistics, and analysis to arrive at business decisions. Business owners are seeing how important and valuable it is to incorporate data analytics into businesses. They are realizing the value of this knowledge and how they can use it to accelerate their businesses.
Needless to say that an employee with strong data analysis skillsets is not only in high demand in today’s work job environment but bears a profile that is highly paid and highly secured. There are instances wherein current employers have offered higher salaries to retain data analysts to ensure that they are not absorbed by competing organizations. Therefore, completing a course in data analytics program will be professionally beneficial to the learner in the long run.
Also Read: Real-Life Applications of Data Science in Education
