Data analysis (or a data analyst) and Data Science (or a data scientist) are two different facets of analytics with different objectives, roles & responsibilities. Hence, it is important for the student to first understand the key requirement of each of the two profiles; and make an informed choice on whether they wish to progress towards data analysis or data science.
Data Analysis is a more analytics-centric role wherein both software, as well as analytical acumen of the student, would be tested. The ability to process terabytes of data, design extensive data-lakes, good know-how on database management system, SQL, and churning insightful reports for businesses, etc. are mandatory skills of a data analyst.
The requirement of the Data Scientist is different and relates more to knowledge of statistics, mathematical models as well as scripting languages such as Python, etc. Hence, based on the existing skillsets & interest of the student, an informed decision needs to be made.
There is a certain level of correlation between the two as well as data analysis is an integral part of descriptive analytics while data science forms a part of predictive and prescriptive analytics.
Happy Learning :)
Where can I practice practical Data Analysis problems?
The key factor in finding practical data analysis problems in the online domain is that the data provided in online practical sites such as https://www.kaggle.com etc. are much cleaner and more manageable; whereas the data in real-world business ...
Which is better in terms of salary and long term growth in data science and machine learning.
Data science is a more generic stream of study which encompasses data analysis, machine learning, data visualization, statistical modeling, data engineering, business intelligence, etc. Therefore, from the perspective of opportunities, data science ...
What is a data science pipeline?
Data Science pipeline depends on the particular business or industry as well wherein data science projects are operated. While in some cases, the entire set of steps starting data collection comes under the purview of the data science pipeline; in ...
Is data science better than business analytics?
There’s not much of a difference between data scientist & business analysts in terms of the acquired skillsets & acumen; however, the application of the acquired skills differs. Data scientists deep dive into the technical side of things focusing on ...
Why is data analysis important in business?
Data analysis is important in business to ensure that the same mistakes are not repeated, and the business can tailor in historical performances in designing future strategies and formulating the business plan. Descriptive analysis provides a view of ...