Basic requirements for a Data Scientist

The companies collect and save large amounts of real-time data every day. What do they do with it then? With unstructured and structured data flowing in at high volume and high velocity, a data scientist has to make the right connections and extract insights from the data and translate it into major business reports. It’s not as simple as it sounds. A typical data science pipeline gives an idea of the flow of processes involved right from obtaining the data to making the desired predictions and calculations.

What is involved?

Database management skills are needed to extract data either from the internet or external/internal databases. This data has to be extracted into a usable data format. The data is then cleaned or scrubbed which refers to filling in missing or empty values, removing anomalies, ensuring the data consistency etc. Now the data patterns can be observed and different types of statistical modeling and visualizations are applied. This can be called as exploratory data analysis. Patterns and trends which can be converted to business value have to be identified at this stage.

The next stage is called modeling and it uses machine learning as a tool. Many different algorithms are readily available and the data scientist has to find the right one that best fits the business needs. This is the stage where past data is used to make future decisions. A statistical model is used as a predictive tool to enhance decision making.

Skills required

Expert knowledge of programming languages such as Python, SAS, R, Hadoop, Spark, SQL etc. is needed. Machine learning skill is most essential for a data scientist. An extensive base of Statistics, Calculus, Linear Algebra etc. is a major asset. Many data visualization tools are available, like Tableau which make analytics easy for executives, analysts, and the data scientist.

What course to study?

The important building stone of Data Science training is the data computing techniques as well as data manipulation and analysis software programs. A prospective Data Scientist has to be ready to invest in learning the specific skill sets needed for the intended field of research so that they are thorough with it. The next step is to be proficient in the required toolsets and platforms so that they can apply their analytical skills to real problems and come up with some amazing results. Good working knowledge in Mathematics and Statistics, as well as coding experience, are very much needed.

Who can learn?

The essential requirements looked for in a Data science trainee is the ability to think out of the box and direct one’s intellectual curiosity, inquisitiveness and argumentative nature into the right channel. They should have the right business acumen too to achieve the required end result. They should be prepared for a new learning process and ready to evaluate and reconsider their prior assumptions and let the data itself guide them to the right solutions. Analytical creativity is what is needed to forecast future business patterns from the past and present dataset available.

Is Data Science your field of interest? Do you have what it takes to be a trendsetter in the field? Enroll in the data science training in Bangalore by ExcelR to enhance your technical skills!

Source : http://datasciencetrainings.bravesites.com/blog