The real-life world is filled with problems and solutions are found day by day. There are many obstacles faced every day. There has to be tackled well. When it comes to technology or any field of business this problem persists and they need to be addressed as soon as possible and to find out the solutions at the earliest. The experts solve problems with the help of statistical, mathematical, and analytical skills. They are called data scientists. Data scientists are experts in the field of analytical data. These experts use their technical skills to solve complex problems. They use computer science, and mathematical and statistical elements to solve problems. Data scientist collects a huge amount of data and analyze and interpret it to get meaningful results. They use these results to get insights beyond statistical analysis.
Role of Data Scientists
Data Scientists work closely with the business. They are working closely with the stakeholders of the business and the heads of the business. This helps in understanding the goals of the business. This helps in determining how to achieve the goals of the business. A data scientist collects huge data and studies it and uses relevant data analysis tools to get better insights. The role of data scientists is:
- Collect data from various sources
- Converting data into useful information using programming tools
- Building project models to get insights
- Creating a visualization of data to convey information to stakeholders
- Maintaining and analyzing data insights
- Utilizing Machine learning tools
- Extension of company data with the third party for information gathering
- Measurement and improvisation of results
- Enhancement of data collection procedures
- Creation of automated systems
- Creations of data dashboards, data visualization, graphs, etc
These are the key roles of data scientists in every business. A day in the life of data scientists includes so many tasks. They have to pull, merge and analyze the data gathered. They need to look for the patterns and trends which is occurring around them. They have to meet the clients to understand the requirement of the projects. They have to explain the project requirements to the team by holding meetings. They are the persons who determine the tools for the project and the creation of the timelines. Data scientists are also responsible for designing, building, and maintaining relevant and useful databases.
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Skills Needed for Data Scientists
As we already said data scientists needed to possess some essential skills to get meaningful insights. These skills can be divided into core skills, Key skills, and Non-technical skills. Let us look into them.
1. Core Skills
- Ability to prepare data for effective analysis
Data Scientists need the ability to prepare data that intend for the effective analysis of the same. The data will be structured and unstructured. Data scientists need to analyze these data and use them for analysis.
- Ability to support self-service analytics performance
A data scientist must aware of the analytics tools used and the performance of the same. They need to have a basic understanding of the tools used for analysis.
- Ability to write codes
Data analytics is done with the help of programming tools. So a data scientist needs to be aware of writing and maintaining the codes.
- Ability to use mathematics and Statistics
Data scientists use mathematical and statistical tools to perform data analysis and thereby find out the insights. So the data scientists must be aware of applying mathematical and analytical tools.
- Ability to support AI and Machine learning
Machine learning frameworks and Artificial intelligence tools are a must to handle the huge data and make insights from it. So data scientists must be able to handle AI tools and machine learning frameworks.
2. Key Skills
- SAS
SAS is software that is needed for data scientists to handle the huge data. It is one of the most commonly used software globally by almost all companies. It is used for information management and advanced analytics.
- MATLAB
MATLAB is a statistical computing software. It has huge add-ons for data analysis. It helps in the implementation of algorithms, plotting of functions and data, matrix manipulations, etc.
- R Programming
It is an open-source programming language. It is statistical computing and graphics. This is a programming language that is used mainly by data miners.
- Python
Python is one of the most common programming languages. In data science, Python is an inevitable language. It is also used by Google, quora, IBM, etc.
- SQL
It is a database management language that is for a relational database. It is one language that is needed to learn and used by data scientists.
- Hadoop
It is a tool that is used for processing big data. It is a Java-based programming language. It helps to process big data in a disturbed computing environment.
3. Non-technical Skills
- Business Awareness
This is a common skill needed by data scientists. They need common business awareness to get insights by analyzing the data. Data scientists need to understand the business, the problems in it, the solutions suitable for the problems, etc.
- Communication Skills
This is one of the most needed and important skills for every data scientist. They are not only dealing with the data analysis, they have to convey the results and thoughts to their team and also to the business stakeholders. So data scientists must possess strong communication skills.
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Conclusion
Data Science is a field that is very important in every field of business. It helps in collecting the data and is used to get insights based on this. Data scientists help in finding trends and insights which is used to solve complex problems.
