Data Quality




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E.g., 2017-01-24
E.g., 2017-01-24
E.g., 2017-01-24
Jan 30th 2017

In this course, the second in the Geographic Information Systems (GIS) Specialization, you will go in-depth with common data types (such as raster and vector data), structures, quality and storage during four week-long modules.

Average: 4.6 (5 votes)
Jan 23rd 2017

Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life. By contrasting the ideal, you will learn key concepts that will help you manage real life analyses.

Average: 6.9 (8 votes)