Introduction: Data Science is a Multi-disciplinary domain which uses various algorithms, scientific processes and developments to extract useful and meaningful Data. In simple words, Data Science is all about discovering unique content from all the structured and unstructured data present by using different techniques. Which is processed through programming, Analytics, and Business Intelligence. The data extracted is mainly for Business decisions, predictions, predictive analysis, perspective analysis, Marketing, and Machine learning.
Data Science with languages: Python is the most used languages in Data Science. It is an extremely popular multi-purpose language which is widely used in the Data Science community. It is also known that 65% of data scientists use python because of its simple usage process. Other languages are also widely used mainly R for data science. Coming to “R” it is an object-oriented language which provides operators, functions, and objects that allows users to explore and analyze data visually. Moving into SQL, It is the most important amongst all the languages. Without Database Data Science is meaningless. SQL is used in structuring the data, data manipulation. Further, the data in SQL is dynamic which means it can be modified and manipulated at any given time.
Data Warehouse is a collection of data from multiple sources. It essentially combines data from several sources into a simple comprehensive and dynamic database. The main purpose of Data Warehouse is to store large amounts of data and to enable quick, complex queries across all the data present in the warehouse which typically uses Online Analytical processing. It is primarily a decision support system which stores historical data across the business- processes it. This processed data is used in High-level business analysis, critical business decisions and more importantly for creating reports and dashboards.
Machine Learning: Being a model of Artificial Intelligence Machine Learning has been a core part of Data Science. Machine learning is a term closely related to Data Science. In simple terms, Machine Learning is the ability given to a system to learn and process the data without human intervention.
Need for Data Scientists: Virtually every industry either service or business needs Data Scientists. The need for Data Scientists is huge. Every decision in an organization depends on Data Science and Data Scientists. To interpret all the data received data into useful business decisions and analyze the return over the investment. On average, According to Linkedin salary a Data scientist earns around $110000/ year. To take up Data Science as a career you can start with signing up for Data Science course
