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2016-09-23

The Little Data Science Checklist


English: Random data points and their linear r...There are lots of sources online and in book stores that will teach a person how to do Machine Learning, Regression, Text analysis, or any other fascinating topic related to Data Science.

But is that all there is?

Just know apply an algorithm, and you improve the bottom line of your company?

What if you need to justify a project? How do you demonstrate that there is a process that can be followed for data science?

Recently with some colleagues we were discussing this precise topic.

Here is the answer that we came up with:



Question:

            What is the question?

            Who asked the question?

            When do they want it?

            How does it provide business value?

Hypothesis:

            Validation Criteria

            Identify the data

            Collect the data

            Transform, Merge, Munge

            Analyze and explore

            Iterate

            Peer Review

            Visualize and Communicate

            Generate new directions.

            Produce Finding

Finding:

            TRUE

            FALSE

            Inconclusive

            Experiment Required

Supporting Data:

            Raw Data

            Chart
            Visualization

I will pick a section and write more about each of these sections, but this little checklist is a beginning step in applying a Data Science process for an Enterprise. 

1 comment:

  1. Hello Doug.
    The Article on The Little Data Science Checklist is nice.It give amazing information about it .Thanks for Sharing the information about Data Science. big data scientist

    ReplyDelete