From our childhood, we have heard that we are nothing without water and water is our life. But in this modern technical era, the same thing can be said about data. Data means information that is basically created from a source and flows to a receiver. Every object, living or non-living is enclosed by various kinds of data. We work only with the data which we can understand and the rest of the data remains a mystery. It is impossible to work with lots of data simultaneously. This is the part where data analytics plays an important role.
A data analyst is a person who is in charge of collecting and analyzing the data. The development and testing of the analytical models based on the collected and analyzed data are also done by the data analyst.
Now let’s talk about the basic requirements and the process of data analytics. First of all, the raw or unstructured data from various sources is collected and then combined into a common format. This data is then loaded into a data analytics system such as a data warehouse, a Hadoop cluster, etc. Then data cleansing and profiling are done to make sure that the data is error-free and consistent overall. After that, the main operation in data analytics is performed i.e. building an analytical model of the data using various programming languages such as SQL, Python, Scala, etc. Finally, the analytical model results are used with the help of data visualization, to make decisions and obtain the desired results.
Career Opportunities in Data Analytics
In this digital age, data analytics is more important than ever. There are multiple jobs opportunities in various industries with the demand for data analytics professionals increasing day by day. Some of the career opportunities that require data analytics professionals are given as follows:
- Data Scientist
A data scientist collects and analyses that data so that the relevant decisions can be made using data visualization. A holistic view of data, good knowledge of data analytics and data visualization skills, as well as knowledge of programming languages such as SQL, Python, Scala, etc., is a basic requirement for a data scientist.
- Data Engineer
A data engineer helps in the design, implementation, and optimization of the data infrastructure that is around the various data analytics processes. In general, a data engineer handles quite large data sets and often helps in making this data readable for data scientists by data cleansing and profiling.
- Business Analyst
A business analyst helps in solving the business problems an organization is facing by using data analytics to understand the business models, company reports, technology integration documents, etc. and provide various business strategies
A statistician collects, analyses and interprets statistical data to obtain coherent and useful information. Some of the common jobs of statisticians are to provide statistical simulations, mathematical modeling, analysis and interpretation of various survey results, business forecasting on the basis of data analytics, etc.
- Machine Learning Engineer
A machine learning engineer analyses and interprets algorithms and statistical models for machine learning using data analytics. Mainly knowledge of both programming and statistics is required for a machine learning engineer.
- Quantitative Analyst
A quantitative analyst helps in solving the various financial problems by using data analytics to analyze large amounts of data to understand financial risk management, investment patterns, exchange rate trends, the stock market, etc.
These are just some of the career opportunities that require data analytics. However, data analytics, in general, is a vast field and the opportunities it provides are endless. There are many more career opportunities and chances in the data analytics field with even more growth predicted in the future. So a career in data analytics is a lucrative prospect with enormous scope and growth in the future.