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Data profiling gives visibility to data quality issues


Katie Slattery 2 minute read Data quality

The chief benefit of data profiling is that it helps you see things that are, to all intents, invisible to the naked eye. In doing so, you get a clear, more comprehensive picture about where you stand.

This allows you to establish, for example, the positives and negatives of your asset – you examine, you gather, you analyse and then you determine, based on the results, your current position.

Data profiling ensures, very effectively, where you stand in terms of quality and, in turn, you can then re-evaluate where you are falling short on excellence – i.e. what is hampering operational processes and/or performance.

The tools that underpin data profiling can be a great benefit in this regard. It helps organisations achieve more substance when it comes to identifying and documenting the scale, impact and cause of these issues.

At the core of this technology is the ability to spot the main issues behind poor data quality and, from this point onwards, understand how widespread and invasive these glitches are.

In short, you become aware of things that you had no idea existed – data profiling allows you to increase your scope and focus on areas that you may ordinarily have overlooked.

A case in point is that you think an issue is concentrated in one department or from a particular source of data. While the crux of the problem may well be concentrated here, the fault may be present beyond the core.

With data profiling you get to uncover the full and true extent of where you are going wrong. From this point onwards, building a business case for fixing it is much easier – your return on investment is enhanced processes and savings to name but a few.

After all, data profiling has the potential to be transformational and set a new benchmark in deliverability, efficacy and innovation. In utilising these tools you root out the factors that impede productivity and quality at every level.