More data means more complexity. While the term “big data” is no longer in vogue, every organisation is being swamped with new sources of information, growing at an ever-increasing rate.

The business case for data quality is clear, with trust big data is useless.

A SearchCIO article asks “When does more data trump clean data?”

The article highlights a common misconception used by the “dirty data” argument, starting with the line “The days of scrubbing data until it’s squeaky clean are quickly becoming a luxury“

What is data quality?

#DataQuality is not, and never has been, about data being squeaky clean

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Data quality is about ensuring that data is fit for purpose

In his response to the question Greg Pfluger, SearchCIO’s expert in this case illustrates this with three examples.

In one case, data can be of relatively poor quality (high-level insights), in the other two information quality is important to ensure that business goals are met.

More data is not better

Adding more data that is not fit for purpose adds complexity, not value. Tweet this

Adding more, poor-quality data is good for the storage and analytics vendors but it may not be good for your bottom line.

What level of quality is good enough?

Pfluger’s conclusion – there is no standard answer for what level of quality is good enough for your business needs, but some level of quality is necessary for most business purposes.

A sound data strategy will provide you with the data governance framework to categorise different data according to its use and importance. You can then plan to put the correct levels of data quality in place, based on what is right for you. Data governance has been shown to have a positive impact on big data  analytics success as discussed in Big data, Quality matters

And, in the era of big data, preparation is key. In our post on how to prepare for big data we explain how to anticipate challenges and seize opportunities.

Not just about BI

Ensuring successful BI projects is not the only reason to govern big data projects.Tweet this

As discussed in Does poor data governance make you a Target the inappropriate use of big data can have devastating reputational and financial consequences.

The debate is not about More data vs Clean data. It is about the appropriate use of data.

Data governance and data quality are what ensure that your use of data is appropriate

Now explore other big data myths and their reality. Separate fact from fiction to navigate the big data landscape effectively.

Image sourced from http://en.wikipedia.org/wiki/Waste_management