Introduction to Data Science Career
Data Science is a career where complex problems need to be solved by analyzing the data. It is a fairly complex field where Scientists work with millions of data points across business, Healthcare, etc. In today’s world, data plays a vital role as Organizations, Individuals, Institutions; everyone is more or less related to data in their day-to-day dealing, and the volume of data increases as ever. As the volume of data grows every second, the most important issue that should be tackled is storing and processing it. In a traditional Relational Database Management System, the data was structured, and the volume of data was less in comparison to the huge volume of data we encounter today. Nowadays, the data can be structured, semi-structured, and unstructured thanks to advanced technology and various sources like Social Networking Sites.
Moreover, the structured data was analyzed using Business Intelligence tools, but when the unstructured or semi-structured data comes into the picture, the same method cannot be flexible. As the data becomes complex, we need complex tools to analyze them. Data Science is the answer to the analytics involved with complex data such as unstructured and semi-structured data. From self-driving cars to understanding customers’ buying patterns, Data Science Career offers the solution of handling such complexity in data and improving their business.
Education required for building Data Science Career
To have a career in Data Science, one should have a Bachelor’s or Master’s Degree in a field related to it, such as Computer Science, Mathematics, etc. In addition, the person needs to work with data points in Business, Healthcare, etc. and should be very keen on learning, curious to explore the complex issues and be able to visualize the data by using highly advanced algorithms, which will help the organizations in determining the statistics and pattern useful for the business.
The skills required for Data Science careers are SQL, statistical analysis and Microsoft Excel. In addition to these skills, programming languages like R and Python and skills in visualisation tools like Tableau can be very useful.
- SQL is one of the essential components of working with Data Science as, without a Database, we cannot access or analyze the data. So having good hands-on in SQL is a must for Data Science.
- Microsoft Excel is a fundamental tool used to analyse the data with many in-built program tools like a pivot table, which summarises and re-organizes the data.
- Python and R languages in Data Science help in analyzing and applying statistical techniques. Also, they help in Data visualization, which helps communicate the information clearly and more efficiently.
Career path for Data Science
As we have already discussed the importance of data and its growth every second, it is needless to say that Data Science Career comes with exciting career paths for professionals. It is a career with multiple roles as it is a combination of many different fields. Roles for Data Science can be programmers, analysts, and statisticians, etc. Data Science’s opportunities are plenty these days due to the massive volume of data and the need to analyze, which adds great value to the business.
As Data Science Career is a field of diverse roles, the various job positions are Business Intelligence Analysts, Data Analysts, Data Mining engineers, Data Architect, Data scientists, etc.
- Business Intelligence Analysts need to understand the functions involving business and be expected to perform data analysis, data mining, etc. The Business Intelligence Analysts help the organization improve its position by figuring out the data patterns by analyzing its data.
- Data Analysts help examine the raw data to produce meaningful results with a programming language and analytical tools. The basic responsibilities involve cleaning and maintaining data and then analyzing the data to present it.
- The Data Mining Engineer’s role involves using advanced algorithms for analyzing the data of their organizations, along with the third parties involved.
- Data Architects are responsible for designing the blueprints for integrating, maintaining the data sources by working with the designers, developers, and users.
- Data Scientists spot the trend by analyzing the large volume of data to carry out further analysis. This provides a deeper insight into the data. Data Scientists work with both the Business and IT to analyze the datasets, understand the data, and resolve complex business problems.
The data volume is growing so quickly that the Data Science Career path’s role will be vital as analyzing the data will increase shortly. Globally, the demand for Data Science increases, and per annum, the average salary paid to Data Scientists is approximately $10,000(US). As data scientists bring great value to the data, the organizations also encounter Big Data’s importance. Therefore, as the demand for professionals is high, the expected salary for Data Science Career professionals remains high.
With the boom of Big Data, organizations are hiring more and more data professionals. The Data Scientists will have a bright and promising career as the demand for professionals increases every day. In addition, many organizations depend on Big Data to improve their business and provide better customer service, so it has great career prospects.
With the popularity of Big Data technology and as Data is of utmost importance to organizations depending largely on the huge volume of data they receive to gain insights. Data Science is a combination of programming skills, statistics, knowledge in modeling and algorithms, etc. Therefore, the opportunities in this field are numerous, and professionals in this field are sure to prosper in their careers.
This is a guide to Data Science careers. Here, we have discussed the education, skills required, job position, salary, and career outlook in Data Science. You can also go through our other suggested articles to learn more –