In literal terms, Data Analytics or Data Analysis means to analyse the data and produce or interpret results. Data analytics refers to the technological field where the data that is generated is extracted, enhanced and analysed using quantitative and qualitative techniques and thereby interpret results. Such results are important in various fields of Management like decision making. In simple words, data analytics simply involves the processing of the already available or generated large amounts of data by analysing their pattern or trend and deriving meaning for better future results. It is a majorly a field of Science and Engineering or Statistics, but is widely recognised as mandatory to-have skill as required by every manager in any industry. The study includes the basic skill set requirement of Mathematics, Statistics, Quantitative Techniques and some basic knowledge on Programming languages like R, Python, SQL, Scala, etc.
Scope of Data Analytics
The amount of data that is created each day through the world network is enormous. With the huge amount of data that is being generated throughout the world, which is termed as ‘BIG DATA’, the field of Data Analytics has grown to include wide scope. New age technologies like Artificial Intelligence, Machine-learning, etc. are to a great extent dependent upon the results obtained through Data Analysis. For example, in the creation of a humanoid (robot like humans), it is the role played by data analytics, used in the artificial intelligence, that predicts the response to be delivered by the robot to a particular stimulus. The various decisions made in the management of different projects depends upon the past or previously available data. This data is implemented to produce useful meaning or solution to the problems. Thus it is evident that Data Analytics has wide scope almost all domains or industries.
Subjects based on which Data Analytics relies
The role of Data science has expanded to a huge scale today. Data collection is the initial process in Data Analytics. This is primarily the role of Data Scientists who identify and gather information relevant to their application and then work with IT professionals or data engineers to combine and use the data. This data is transformed into a common format to be fed into analytics systems such as Data warehouses, Hadoop cluster, NoSQL database, etc. After this, certain programming languages are used to design an analytical model. Thus we see that the field of Data Analytics basically involves the knowledge and application of the following subjects and skills–
Types of Data Analytics courses and Applications
The two basic domains of Data analytics can be categorised as Exploratory Data Analysis (EDA) and Confirmatory Data Analysis (CDA). EDA deals with determining the data patterns, trends and relationships in the available data collection. Its aim is to perform a detective work. CDA on the other hand deals with deriving interpretation or checking if the validity of a hypothesis holds or not.
Another classification of Data Analysis could be based on Quantitative or Qualitative techniques used in the analysis. Quantitative technique involves more of statistical solutions and data, whereas Qualitative technique includes more of interpretative solutions even based on non-statistical data like images and videos, etc.
Apart from the above, Data Analytics is studied as part of Management subject called as Business Analytics. Business Analytics involves the usage of the basic analytical principles and tools to derive and predict the best decisions to be taken in business. The role of BA is another predominant role of the century aspired by the youngsters in the world.
Benefits of Studying Data Analytics abroad
The number of Indian students studying in the US, especially in the field of Science and Engineering has declined to some extent as a consequence of the Visa-tightening norms by the Trump-administration. American universities find it difficult to include diversity in their classroom programs. The ‘USA Today’ report declared a 6 percent decrease in the international graduates in 2016-17. With this on one hand, and the growing demand for the role of Data related job-roles on the other, there is a dearth for students graduating from these degrees. Hence taking up courses in Analytics still holds a great deal of opportunities for the aspiring students. Hence though Big-Data analytics is still a demanding job profile, there is still a gap in the availability of the suitable workforce skilled in the stream. It is mostly the post-graduate programs such as degrees or certificate programs that are more popular and in higher demand among the students wishing a career in the field.
Having said this, one of the major hindrance or drawbacks to the course on Data Analytics could be the high cost of doing the course abroad. But taking up short-term specialization courses like Certifications could help the students looking for the study abroad. Moreover, considering the ROI of the program, it is a positive outlook that the study provides.
Top Universities and courses in Data Analytics (by ranking)
Job Prospects and Future Opportunities
As discussed before, we come to understand the various demanding job prospects in the field of Data Analytics. According to recent reports, Big-Data is growing at a very high speed, with nearly 2.3 trillion GB of data produced every day, and the data galaxy doubling every couple of years. With such a huge generation of data, there is huge demand for people skilled in the Data Analytics field to analyse and process data to produce the desired results in any field. There are a plethora of opportunities and job roles offered by doing courses in Data Analytics. Some of them are as follows –
According to the US Bureau of Labor Statistics, recent reports also convey that there will be a job growth by 4.4 million in the Big Data field by 2024. This is aided by the evident skill-gap in the field. A report in 2014 showed that 41 percent of businesses faced major challenge of integrating big data into their operations due to the lack of skilled candidates.
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