Article published by : prashanthbabu on Monday, November 20, 2017 - Viewed 144 times

Category : Software

Difference between Data Scientist and Data Analyst



There are multiple openings for job titles like Data Scientists, Data Analysts, and Data Engineers. Though a majority of these activity titles cope with records and sound comparable, they do have a number of differences. Ever questioned how specific they may be from each other? I did! And right here are the variations I observed among a Data Scientist and a Data Analyst. First we’ll get to know the difference between data science and data analytics.

Data Science
Data science is a minimum large amount of structured and unstructured data to identify patterns Including a combination of programming,statistical skills,machine learning & algorithms.
Data scientist: Mainly looking at estimating the unknown, e.g.
Building statistical models that make decisions based on data. Each decision can be hard, e.g. block a page from rendering, or soft, e.g. assign a score for the maliciousness of a page, that is used by downward systems or humans.
Conducting causality experiments that attempt to attribute the root cause of an observed phenomenon. This can be done by designing A/B experiments or if A/B experiment is not possible apply epidemiological approach to the problem.
Identifying new products or features that come from unlocking the value of data; being a thought leader on the value of data. A good example of that is the product recommendations feature that Amazon first made available to a mass audience.

Data Analytics
Data analytics is a process and perform statistical analysis of data discover how data can be used to draw conclusions and solve problems.
Data analyst: Mainly looking at the known, i.e. historical data, from new perspectives, e.g.
Writing custom queries to answer complex business questions.
Conceiving and implementing new metrics on capturing previously poorly understood parts of the business / product.
Addressing data quality issues, such as data gaps or biases in data acquisition.
Working with the rest of engineering to instrument incremental new data acquisition.
What Data Scientists do ?
They predicts the future based on past pattern
Explores and examines data from multiple disconnected sources
Develop new analytical methods & machine learning models
What Data Analysts do ?
They acquire data ,process data and summarize data
Package data for insights
The do design and create data reports using various reporting tools
Data science is used in
search engines,
Financial services and
ecommerce.

Data Analytics is used in

Health care
Travel
It industry
CONCLUSION:

Regardless of the similarities and differences between a data analyst and a data scientist job role, one is incomplete without the other. 2018 is the best time to master anyone of the course.


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Keywords: data science, data analysis, skills reuired for data scientist

By: prashanthbabu

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