How useful is time series analysis in data science?
The usefulness of time-series data or cross-sectional data in data science depends largely on the objective of the research. For example – analyzing the effectiveness of marketing campaigns does not require time-series data as it is a one-time affair. However, considering both descriptive as well as predictive analytics on historical data trends & patterns; time-series data is extremely important.
A perfect example of the same is in any business wherein a customer journey is tracked and analyzed and the probability of a prospect getting converted to the customer is devised. Also, it's heavily used in Financial Applications such as predicting the Future Stock prices based on the historical data.
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Would it be better to first learn Data Analysis or Data Science.
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 ...
What is a Data Analysis pipeline?
A pipeline, in generic terms, refers to the series of steps via which a particular data or input passes through to get processed into the final output. Data Analysis pipeline also follows the same definition as it involves all steps starting from ...
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 ...
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 ...