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One framework that can help data scientist carry out their work is the OSEMN Framework. OSEMN are clear stages or sequences of activities that are important in a data science process.
The OSEMN framework contains various step-by-step alias step carried out by data scientist.
Starting from data collections, data preparation to data interpretation. This framework can be useful framework for solving problem in the field of data science analysis.
It could said that of OSEMN stages very coherent so that if one of the stages is missed or missing the conclusion cannot be drawn.
In the bellow is explanation about OSEMN:
1) Obtain
Gather the data
Determine what data would be useful
Evaluate what data are available
Decide on how the data can be gathered
2) Scrub
Clean the data to prepare it for analysis
Correct inconsistent formatting
Remove duplicate records
Handle missing values
Remove inaccurate information
3) Explore
Search for interesting patterns and statistics that stand out
Examine variable distributions
Examine variable relationships
Perform statistical tests
4) Model
Generate predictions and insights
Select a model type for your goals (often in cooperation with a partner)
Categories of models include:
Classification - Is this “A” or “B”?
Regression - How much or how many?
Clustering - What natural segments can we find in our data?
5) iNterpret
Help others to understand the results of your analysis
Build visualizations
Construct stories
Create presentations of your findings
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