Data science is the area of analysis that involves extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes. It helps you to discover hidden patterns from the raw data. Every organization is looking for candidates with knowledge of data science.
Data Science is a concept that unifies statistics, data analysis, and their related methods to “understand and analyze actual phenomena” with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, domain knowledge, and information science.
Data science is a multidisciplinary field that uses tools and techniques to manipulate the data so that you can find something new and meaningful.
Let’s have a look at its components and roles-
Components of Data Science
Data Science consists of three main components including data organizing, packaging, and delivering or OPD data. Let’s have a look over it one by one…
Organizing the Data-
It is the planning and execution of the physical storage and structure of the data that takes place after applying the best practices in data handling.
Organizing the data is a practice of categorized and classified data to make it more convenient and easy to use. The important documents should be arranged in a logical and orderly way.
Packaging the Data-
The packaging is a combination of the database with Metadata that describes the dataset. The main purpose of data packaging is to provide sufficient and contextual data to make data usable to others as well. It involves aesthetically modifying and combining the data in a presentable form.
Delivering the Data-
Data delivery is the process of transferring campaign data out of the Oracle Data Cloud platform and into your cookie or profile store or to a partner. It makes sure that the outcome has been delivered to the concerned people.
Different roles in the Data Science Industry
1 Data Scientist-
A data scientist’s main intention is to organize and analyse vast amounts of data, often using software specifically designed for the task. Data analysis depends on their industry and the specific needs of the business or department they are working for.
2 Data Analyst-
A data analyst is someone who explores information using data analysis tools. The meaningful results they pull from the raw data help their employers or clients make important decisions by identifying various facts and trends. A data analyst is a master of languages like R, Python, SQL, and C. Main responsibility is collecting, processing, and performing statistical data analysis.
3 Data Engineer-
They are software engineers who design, build, integrate data from various resources, and manage big data. A data engineer is a master of Hive, NoSQL, R, Ruby, Java, C++, and Matlab. It would more convenient for him/her if they can work with popular data APIs and ETL tools, etc.
4 Data Architect-
Data architects are senior visionaries who interpret business requirements into technical requirements and define data standards and principles. The data architect is responsible for visualizing and designing an organization’s enterprise data management framework.
The data architect masters technologies like Hive, Pig, and Spark, and needs to be on top of every new innovation in the industry.
5 Data Statistician-
The Data statistician collects, analyses, understand qualitative and quantitative data by using statistical theories and methods. The data statistician masters technologies like SQL, R, Matlab, Tableau, Python, Perl, Spark, and Hive.
6 Machine Learning Engineer-
Machine learning engineers feed data into models defined by data scientists. They’re also responsible for taking theoretical data science models and helping scale them out to production-level models that can handle terabytes of real-time data. SQL, REST APIs, are ordinary technologies that are in line, and machine learning engineers are also expected to perform A/B testing, build data pipelines, and implement common machine learning algorithms such as classifications, clustering, etc.
7 Business Analyst-
A Business Analyst is a person who analyses an organization or business domain and documents its business, processes, or systems, assessing the business model or its integration with technology. To be a master as a Business Analyst one need to know the technologies such as SQL, Tableau, Power BI, and, Python.
Final Words
Data Science is such a great career; it comes with huge market demand. As we know most of the organization looks for candidates with great knowledge of data science. If you are looking for your bright career in the field of Data Science, you are in the right place for Data Science Course in Noida.
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