Unsure how to prepare data for analysis?
Data structuring is the second step of the data journey.
It involves the process of organizing and ‘cleaning’ your collection of data with the aim of producing a single data source accessible across the business, ensuring consistent reporting.
Without structure, your data is inconsistent and meaningless.
Removing outliers or data entry errors, infering missing data where possible, and formulating information of interest (such as time in system from time leaving the system minus time of entry) is important to obtain a quality dataset, and therefore achieve correct outcomes.
If set up right, data can be used to benefit and empower teams across your business. It’s important to provide a quality source with key measures of success calculated using the same methodologies that can be quickly and efficiently exported and used to take action.
Let’s Talk Data Structure.