Data science tutorial: the complete guide for beginners
Table of Contents
- Role of a data scientist
- Becoming a data scientist
- What tools are available for data science?
- What is the salary earned by a data scientist abroad?
- What is the salary earned by a data scientist in India?
- What are the general responsibilities of a data scientist expected by companies?
- What does the future hold for data science?
OverviewData science is a field of study where data is analyzed using some specific parameters and a decision is taken based on the pattern and results that are generated by the analysis. It is an interdisciplinary science that is about using scientific methods, algorithms, and processes to study the available data and gain knowledge from it. Data science is a mixture of concepts that unify data, machine learning and other useful technologies to derive some meaningful results from the sample data. It is used as a synonym for many related fields like business analytics, business intelligence, predictive modeling, and plain statistics. It has many concepts taken from earlier solutions and rebranded as a part of Data Science. It is a very sensitive field as there is a big catch- without proper utilization of resources and poor management, data science is bound to give results that are spectacular failures.
Role of a data scientistA data scientist makes use of the data available to get tangible results that can be used to improve the functionings and performance of an organization. They collect information from a variety of sources. Then they analyze this data with various methods and generate patterns and trends. These results are then used to give the organization a set of recommendations and a plan of action for the future. These once implemented are again monitored, measured, and analyzed to track its efficiency. This ongoing process is continuously carried out by data scientists to optimize the existing system. When necessary, they also build ML and AI-based tools for utilizing the data. They also store all these data and clean it up before doing any analysis. In addition, data scientists are also expected to train various teams to internally handle some analytics process. A data scientist is an in-demand job and is a good career path. It also pays really good salary. If you want to become a data scientist without a higher education degree, then there are a few options that can choose. Bachelor degree is now introduced for data science. You can choose to go for it. But if you want to do it faster, then you can do an offline course on data science. If that is not possible, consider doing an online course on data science to get the required certification. How businesses use data science to their benefit? There are a whole lot of ways data science usage benefits businesses. A few of them are discussed in this section. Making better decisions at every level of management Data scientists are strategic partners to middle and upper management. The data scientists measure, track, and record performance parameters. With these metrics, the data is used to improve the decision-making process at multiple levels of the organization to effectively raise the overall performance of the organization. Decisions on recruiting This is a great application of data science. All that time saved in reading resumes can be contributed more effectively to the organization. using data science, it becomes easy to weed out unwanted or unsuitable applications for a job listing. With all the information available on the web, the data scientist can work towards finding the best and (nearly) perfect candidate for any position. Defining goals and objectives After analyzing the data and coming up with trends and patterns, the data scientists give recommendations to the team. They also suggest a plan of action based on these trends for better customer interaction, performance, and increase in sales by targeting properly. Identifying opportunities Data scientists also go through the existing system and help the teams optimize the existing patterns for better results. They are expected to constantly improve upon the existing analytics and exploring new avenues and methods for data analysis. Best practices With the data in hand and the results of the analysis, the data scientists are in a unique position to suggest best practices that should be followed by each team to improve on their performance and increase their contribution to the company. In this context, the data scientist takes an effort to introduce the key players to using analytics tools effectively on their end. This can be used for gaining insights on, let's say, a marketing campaign. Identifying changing targets Most companies have a minimum of one channel through which they collect data. Usually, many channels from the analytics tool to survey are used to collect data from the consumers. The demographics and other aspects that are not game-changing on their own are linked and their relationship often provides the key to identifying new targets. The data scientist must be capable of establishing a relationship between seemingly obscure Testing the decisions taken It is the most imperative result oriented task of the data scientist. Impact of every decision must be recorded and analyzed. Not every decision taken will be the best decision despite the maximum effort. Such errors must be rectified and effort will be taken to perfect the solution to every issue faced. In a way, it quantifies success and failures.
What tools are available for data science?A lot of tools are available for a data scientist. The users are expected to find the best fitting stack of data science tools that satisfy the requirements of the company. Check out our article on Data Science tools. Tools to collect data Collecting data is the first step to analyzing the data. The data has to be of good quality to get the best results. More importantly, the integrity of the data, accuracy are important. Additionally, the data should have the least possible errors. The tool that helps us to achieve these goals are used to collect data. Ex: IBM DataCap, Octoparse, OnBase Tools to analyze data The next step to data collection is to process and analyze the data. The results derived from the analysis is then used to make decisions for the betterment of the company. The data analysis is used to determine the performance levels of the company. Ex: Domino data lab, Alteryx, Rapidminer Tools for data warehousing Data warehousing is collecting corporate data and data from operating systems and other external sources. These data are consolidated in a warehouse and made easy to use. Ex: Amazon Redshift , Google Bigquery, Microsoft Azure, SQL Tools for machine learning Machine learning is an important aspect of data science. Machine learning is used in prediction analysis. It is used to evaluate and optimize the data to accurately interpret it to obtain the desired results. Ex: BigML Tools for data visualization There is a need for data analysis results to be presented in a visual format to be easily understood by all people. Data visualization helps with identifying trends and patterns that will help us make educated decisions for any business. Data visualization is achieved through graphs, charts, maps, and others. Google Fusion Table, Microsoft Power BI, Qlik, SAS, D3.js What is the salary earned by a data scientist abroad? In the US, a data scientist earns an average salary of $128,700/- per annum. The highest recorded salary of a data scientist, in general, is $249,000/- per annum. In Australia, a data scientist earns a salary of 120,000/- er annum. The highest recorded salary is 215,000/- per year. In the UK, a data scientist earns as much as a salary of 54,000/- per year. The highest recorded salary is 126,000/- per annum. The salary is subject to education, experience, certification, employer, and the location of the employer. * Source: Indeed. All the salaries average and highest are taken from the set of salaries that were reported to and collected by Indeed . What is the salary earned by a data scientist in India? An entry-level data scientist makes on an average Rs. 7Lakhs per annum. According to payscale, the highest recorded salary is in 1.7M per year. With the right education, experience, job location, and employer, you can earn more salary per annum. What are the general responsibilities of a data scientist expected by companies?
- Collect and store data.
- Process, Clean up and check the integrity of the data.
- Make data secure and in an easily readable format.
- Use machine learning technique for optimization and selecting features.
- Expansion of data collection by including third party data from surveys and other methods.
- Analyze the data and present visual results that are easily understandable.
- Generate patterns and trends based on the analyzed information.
- Chart out a course of action and give recommendations for improvement.
- Build tools if needed. Detect any anomalies with a detection system and monitor its performance.
- Keep optimizing and improving on the existing system and results.