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 fields such as 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 is increasing as ever. As the volume of data grows every second, the most important issue which should be tackled is to store and then process 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 the advanced technology and from various sources like Social Networking Sites, etc.
The structured data moreover was analyzed using Business Intelligence tools, but when the unstructured or semi-structured data comes into the picture, the same method cannot be as 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 understand the buying pattern of customers, Data Science Career offers the solution of handling such complexity in data and help organizations in improving their business.
Education required for building Data Science Career
To have a career in Data Science, it is preferable that one has a Bachelor’s or Master’s Degree in a field related to it, such as Computer Science, Mathematics, etc. 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 along with skill in tools for visualization like Tableau can be very useful.
- SQL is one of the essential components of working with Data Science as, without 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 very basic tool used in analyzing the data with the help of many in-built program tools like a pivot table which helps in summarizing and re-organizing the data.
- Python and R languages in Data Science help in analyzing and applying the statistical techniques. Also, they help in Data visualization which in turn helps in communicating the information clearly and more efficiently.
Career path for Data Science
As we have already discussed the importance of data and the growth of it every second, it is needless to say that Data Science Career comes with exciting career paths for professionals. Data Science 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. Opportunities in Data Science is plenty these days due to the massive volume of data and the need to analyze which adds great value to the business.
Job positions
As Data Science Career is a field of diverse roles, the various job positions are Business Intelligence Analysts, Data Analysts, Data Mining Engineer, Data Architect, and Data Scientist, etc.
- Business Intelligence Analysts need to understand the functions involving with Business, but also can be expected to perform data analysis, data mining, etc. The Business Intelligence Analysts help the organization to improve its position by figuring out the patterns in data by analyzing the competitors’ data.
- Data Analysts help in examining the raw data to produce meaningful results with the help of programming language and analytical tools. The basic responsibilities involve cleaning and maintaining data and then analyzing the data to present it.
- The role of the Data Mining Engineer 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 and help in understanding the data and also resolve the highly complex problems in business.
Salary
The volume of data is growing so quickly, that the role of Data Science Career path is going to be very important as the demand for analyzing the data will increase in the near future. Globally, the demand for Data Science is increasing and per annum, the average salary paid to Data Scientist is approximately $10,000(US). As data scientists bring great value to the data and also the organizations encounter the importance of Big Data, and as the demand for professionals is high, the expected salary for Data Science Career professionals remains high.
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Career outlook
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 is increasing every day. Many organizations depend on Big Data for improving their business as well as providing better customer service, so the Data Science has great career prospects.
Conclusion
With the popularity of Big Data technology and as Data is of utmost importance to organizations depending largely on the analysis of the huge volume of data they receive to gain insights. Data Science is a combination of programming skills, statistics, and knowledge in modeling and algorithms, etc. The opportunities in this field are numerous and professionals in this field are sure to prosper in their careers.
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