Typically, data in data mining has to be cleaned and organized before it can be analyzed. This can include the elimination of duplicate data, cleaning up of inconsistent data, filling in missing data, and merging data from multiple sources. This preparation may have a significant impact on the usefulness of the final results. It's also possible that businesses have to choose the appropriate fields and convert the data into a suitable format. In more complex projects, having the support of experts like Datalance can prove helpful, especially for companies looking to get assistance with structuring larger datasets for meaningful analysis and reporting.