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Browse CoursesData analysis is the practice of working with data to glean useful information, which can then be used to make informed decisions.
By : AWESOME EMMANUEL
Data Analytics & Visualization with Tableau Desktop...
4.8 771
6:1:29 hrs 27 lectures All Level
By : AWESOME EMMANUEL
Complete Data Analysis course with Microsoft Excel...
4.5 715
14:5:0 hrs 47 lectures All Level
By : Anshuman Tandon
Transforming Raw Data into Compelling Visual Stories...
4.8 598
3:3:14 hrs 20 lectures All Level
By : Paul Eastwood Harris
Including 2016 and 2013 ...
4 543
2:54:11 hrs 40 lectures Intermedite Level
By : Theodore Petrou
Continue your data analysis journey with Python by mastering the fundamentals of the ...
4.1 747
2:31:35 hrs 36 lectures All Level
By : Theodore Petrou
Begin your data analysis journey with Python by mastering the fundamentals of the pan...
4.3 599
1:26:56 hrs 28 lectures Beginner Level
By : Ahmad Sharifzadeh
For researchers...
4.1 1080
3:30:6 hrs 45 lectures All Level
By : Junaid Ahmed
Learn Data, and IT Literacy Foundation Skills with live examples on three popular Ent...
4.7 10268
6:49:31 hrs 70 lectures All Level
By : Arthur Fong
QlikView Data Model, Visualizations & Expression in KPI Metrics & Financial Reporting...
4.6 5605
2:29:19 hrs 50 lectures All Level
By : SkillsOnDemand .
Create 6 Excel Dashboards - Learn Excel Data Analysis & Data Visualization with Pivot...
4 17566
5:1:57 hrs 48 lectures Expert Level
4.2 770776 Beginner Level
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Data analysis is the process of inspecting, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making.
In business, data analysis helps identify trends, patterns, and insights from data. It informs strategic decision-making, improves efficiency, and guides business operations.
Data visualization involves presenting data graphically. It aids in interpreting complex information, identifying patterns, and communicating insights effectively.
In research, data analysis helps researchers draw valid conclusions from their findings. It provides a systematic approach to interpreting data, validating hypotheses, and supporting research outcomes.
EDA plays a crucial role in data analysis by uncovering patterns, trends, and anomalies in the initial stages of investigation. It helps analysts form hypotheses, identify outliers, and make informed decisions on further analysis techniques.