Data Spadework for Power BI Visualization

If you have decided to work on a report for your organization or customer, make sure that your spadework is up to the mark. This will help you in saving lot of hassle when making a report or visualization when making without proper spadework.
First of all you have to see what type of control you have on your data source.

1- Full Control
This must not be taken wrongly as this is related to access to data, here it means that how much you can influence the way and form you are getting data for your reports. If you are mandated to implement business intelligence in your company, then you have to set standards for your data. This may fall in data governance domain but to some extent you have to play a role to get data in meaningful format without unnecessary and inconsistent arrangements. This may be very cumbersome to check for the sanity of data after imported in Power BI especially when your data is in bad shape. This may adversely affect your facts and figures and may contribute in raising false flags due to incorrect data. If you have full control on your data then you can easily achieve maximum accuracy level in your reports.

2- Partial Control
When you don’t have much of a control on the way of getting data, you might have to face a lot of challenges in producing quality results. This may be true when organizations are not ready to change the way the data is gathered and produced. This also belongs to change management where organizations are reluctant to experiment new ways because of working culture and limitations in terms of workforce capabilities. In order to minimize effects of inconsistent data format, you need to list down possible variations to cater the same in your queries. Things may be very difficult in cases where consolidation of data is needed. The best way of getting good reports is to ensure that each data provider is ensuring consistent data entry. Proper standards can be enforced when referring similar data like department names and designations where consistent data entry can help in getting correct figures when data is consolidated from different sources.

3- No Control
In cases where you have simply no control on data sources, you have to set expectations correctly with the recipient of these reports. There are always chances of errors especially when data consolidation is required and data is constantly refreshed and updated. Such cases requires constant testing and maintenance if report is not a one off report. Whenever fresh data is imported, proper auditing is needed to check if any real data is ignored by your query rules. This is also true when your report needs data from external/third party sources. If your external source has changed the format of data or moved to a different URL, you will have to go back and fix your reports.

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