Learn about data quality for your BIM Project

BIM is based entirely on the data that it receives and how that data is played along throughout the process. And that is why data plays a crucial role in BIM modeling. It is often heard that data is king and it is true, especially with the construction of buildings using BIM technology.

 The quality of data for BIM Projects is an extremely important aspect to consider. Bad data leads to the failure of the entire project. Hence, taking care of the data quality is necessary, and leads to enhancing the functionality of the BIM method.

What do you mean by data quality?

 

Data quality is a particular level up to which the data showcases its purpose. In other words, when we have certain business goals and they differ from one another, the quality of data is used to represent reality, solve issues and make decisions based on collected data.

Data quality explains the reliability of the data that is collected. To ensure that the data is good or bad, certain measurements and specifications are taken for determining the quality. The following attributes are usually measured:

• Accuracy
• Timeliness.
• Completeness
• Consistency
• Uniqueness
• Format

Explaining these attributes a little bit more so that it gives more clarity:

Accuracy

When the data that is used in the 3D BIM Modeling represents reality, the accuracy factor is checked out.

Timeliness

Due to the continuous changes in data during construction, the data must stay updated.

Completeness

As we know, incomplete data is of no use. It only takes the project in the wrong direction and delays the completion of the project. Thus the data must be completed always.

Consistency

Consistency is something that measures if each occurrence of the data point is the same throughout all the sources. When the data consistency is there leads to the same number for all that is for the facility management software, model, and spreadsheet.

Uniqueness

This attribute is essential in looking at the duplicates in a model. It helps in the unique coding of the components that are used during the later project stages.

Format

There is a certain format for the data entries that is need to be followed. Each element has a certain standard value.

What is the importance of Data Quality?

Unpredictable results and information

With continuous incorrect project data, there are few consequences. Firstly, relying on such data would lead to poor judgment and bad decision-making. The errors in design might result in a waste of time. The quantity analysis will also be incorrect which will delay the project. All of this leads to mistrust in the actual data.

Incomplete data

Many times there are design data that form the base for construction. In case the characters of the data are not complete, that leads to a problem. It stops the contractor from making the right orders for the construction site. Incomplete data also creates risk factors as the contractors might order for less quantity and later on realizes that the incomplete data made them do that. This in turn delays the process even more.

Duplicated data

There are also duplicates in model objects such as one wall that is placed on the other, or in the properties as well. The first one results in wrong quantity take-offs and lists while ordering. And the second one results in improper management of data and a heavier model. 

 

Carrying data quality checks for BIM projects? 

 

 

The attributes that are talked about above, can be very well defined in metrics and they are used for quality checks and set a quality compliance level. As each project has different requirements and specifications it is indeed important to agree on how and when the data checks are done. The more important metrics are included in the weekly checks for BIM Outsourcing, while others can be checked at a less frequent interval maybe once or twice in the entire project lifecycle.

Summary

Once all the checks are done, a complete idea of the project’s progress is received. Keeping a check on the data quality is always a good idea to have a proper update on the project. It might be a time-consuming thing, but in the long run, this can be a great investment.

Many attributes are checked along with BIM coordination. While few there are automated and are automatically checked promptly.

This in turn gives an entire picture of what the data is worth and also the area where there is scope for more improvements. This sorts out the data in the best manner and gives the stakeholders knowledge about required data and bad data. All these lead to great decision-making that further leads to a quality BIM project. This is why it is always advised that every BIM project should begin with a proper and thorough data quality check.