Data Analysis involves extracting meaning and insights from raw data. It involves methods and algorithms that examine, clean, transform and model the data to obtain conclusions.

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Data science continues to generate excitement and yet real-world results can often disappoint business stakeholders. How can we mitigate risk and ensure results match expectations?

Data scientists spend a large amount of their time cleaning datasets and getting them down to a form with which they can work. In fact, a lot of data scientists argue that the initial steps of obtaining and cleaning data constitute 80% of the job.