Data Science vs Computer Science vs Data Analytics - PowerPoint PPT Presentation
Title:
Data Science vs Computer Science vs Data Analytics
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With the rapid development of the technology sector, it can be quite a challenge to keep up with all the niches and stay current on their advancements. Of the many fields that are responsible for the increasing buzz in the sector, Data Science, Computer Science, and Data Analytics are three critical domains that spearhead the revolution in technology. Where do these domains fit in? How do they differ from each other? How would you launch your career in them? While they seem to have many things in common, Data Science, Computer Science, and Data Analytics entail very different things. If you are on the fence about which field to choose, here is an in-depth comparative analysis for you. It breaks down the fundamental differences between the three, the applications of these domains in various industries, the salary trends, the skills you need to springboard your career in these fields, and more. – PowerPoint PPT presentation
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Title: Data Science vs Computer Science vs Data Analytics
1
Data Science Data Analytics Computer Science
2
Data Science
1
Used in large and small-scale data-
Study of Data. Involves storing, procuring, and
organizing data.
driven organizations.
Widely used across business
2
logistics, healthcare, entertainment,
finance, and education.
3
Mathematical approach and
prevents data redundancy.
3
Computer Science
1
Used in all technical organizations.
Study of computation and its applications.
Involves implementing computational systems in
software and hardware.
Widely used across banking,
2
healthcare, business, governance, and
entertainment.
3
Computational approach. Boosts
speed and efficiency.
4
Data Analytics
1
Used in large and small-scale data-
Analysis of data. Involves analysis of raw data
to find answers.
driven organizations.
Widely used across industries for risk
2
detection, tracking customer
behaviour, and security.
Statistical approach. Picks up trends
3
from massive amounts of data
without loss.
5
Data Scientist Skills
1
2
3
4
Data Manipulation and Integration
Statistics and Programming
Machine Learning
Data Visualization
6
Computer Scientist Skills
1
2
3
4
Software Development
Mathematics and Technical Writing
Computer and Technology
Programming
7
Data Analyst Skills
1
2
3
4
Statistics
Programming
Data Management
Critical Thinking
8
Tools Used in Data Science
1
Data Collection Tools (Trackur, Semnatria) Data
Storage Tools (MongoDB, Apache Hadoop, Apache
Cassandra) Data Extraction Tools (Content
Grabber, OctoParse) Data Cleaning Tools
(OpenRefine, DataCleaner) Data Analysis Tools
(Tableau, Python, Orange)
9
Tools Used in Computer Science
2
Linux Commands Text Editor Excel Powershell
PowerPoint
10
Tools Used in Data Analytics
3
RapidMiner KNIME Heap TypeForm Amazon RedShift
11
Salary Trends
Data Science The average annual salary of a data
scientist is 96,491 in the US.
1
Computer Science 72,173 is the average annual
salary of computer science graduates in the US.
2
Data Analytics The average base salary of a data
analyst is 72,945 in the US.
3
12
Read the full article
https//www.greycampus.com/blog/data-science/data-
science-vs-computer-science-vs-data-analytics
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