What is Data Science?
Data science is a deep study of the massive amount of data, which involves extracting meaningful insights from raw, structured, and unstructured data that is processed using the scientific method, different technologies, and algorithms. It is a multidisciplinary field that uses tools and techniques to manipulate the data so that you can find something new and meaningful. Data science uses the most powerful hardware, programming systems, and most efficient algorithms to solve the data related problems. It is the future of artificial intelligence. Asking the correct questions and analyzing the raw data. Modeling the data using various complex and efficient algorithms. Visualizing the data to get a better perspective. Understanding the data to make better decisions and finding the final result.
Let suppose we want to travel from station A to station B by car. Now, we need to take some decisions such as which route will be the best route to reach faster at the location, in which route there will be no traffic jam, and which will be cost-effective. All these decision factors will act as input data, and we will get an appropriate answer from these decisions, so this analysis of data is called the data analysis, which is a part of data science.
Types of Data Science Job
If you learn data science, then you get the opportunity to find the various exciting job roles in this domain. The main job roles are given below:
1. Data Scientist 2. Data Analyst 3. Machine learning expert 4. Data engineer 5. Data Architect 6. Data Administrator 7. Business Analyst 8. Business Intelligence Manager
Below is the explanation of some critical job titles of data science.
1. Data Analyst: Data analyst is an individual, who performs mining of huge amount of data, models the data, looks for patterns, relationship, trends, and so on. At the end of the day, he comes up with visualization and reporting for analyzing the data for decision making and problem-solving process. Skill required: For becoming a data analyst, you must get a good background in mathematics, business intelligence, data mining, and basic knowledge of statistics. You should also be familiar with some computer languages and tools such as MATLAB, Python, SQL, Hive, Pig, Excel, SAS, R, JS, Spark, etc.
2. Machine Learning Expert: The machine learning expert is the one who works with various machine learning algorithms used in data science such as regression, clustering, classification, decision tree, random forest, etc. Skill Required: Computer programming languages such as Python, C++, R, Java, and Hadoop. You should also have an understanding of various algorithms, problem-solving analytical skill, probability, and statistics.
3. Data Engineer: A data engineer works with massive amount of data and responsible for building and maintaining the data architecture of a data science project. Data engineer also works for the creation of data set processes used in modeling, mining, acquisition, and verification. Skill required: Data engineer must have depth knowledge of SQL, MongoDB, Cassandra, HBase, Apache Spark, Hive, MapReduce, with language knowledge of Python, C/C++, Java, Perl, etc.
4. Data Scientist: A data scientist is a professional who works with an enormous amount of data to come up with compelling business insights through the deployment of various tools, techniques, methodologies, algorithms, etc. Skill required: To become a data scientist, one should have technical language skills such as R, SAS, SQL, Python, Hive, Pig, Apache spark, MATLAB. Data scientists must have an understanding of Statistics, Mathematics, visualization, and communication skills.