In this first episode we discuss our perspectives of data validation. This episode digs into data validation from multiple perspectives of the analyst, leadership, data capture and data output.
Robin Hunt of ThinkData Solutions and Oz du Soleil, Microsoft Excel MVP, both live and breathe data! Listen in their conversation if you ever want to find out their takes on the following questions:
What makes a good data analyst? (2:06)
Why have Robin and Oz started this series (3:35)
What is data validation for an analyst? (5:00)
What are some failures in how data can be taught? (6:13)
At what point should a good data analyst start asking questions about the data? (6:45)
How can a good leader identify a good data worker? (9:23)
What does the future data worker look like? (10:40)
Why is data validation important? (11:05)
Why is data quality important? (11:54)
Why is it important to develop processes in data? (15:00)
Why is data cleaning so important? (23:04)
What are some good tips to spot data that needs cleaning? (24:00)
Why is Robin such a record count fanatic? (26:00)
Why should data validation techniques be used at the point of data entry? (29:00)
What does Oz want you to take away from this episode? (33:24)
Both Robin and Oz are LinkedIn Learning Instructors whose courses have been studied by hundreds of thousands of people who are interested in data.