By Naked CIO, 1 June 2009 08:00
COMMENT
Ensuring the integrity of information can make all the difference for your business, says the Naked CIO. So what are you waiting for?
How many times have I talked about the importance of maintaining data integrity?
Here I go again
Poor quality data input and controls are a commonplace workplace challenge and yet there still seems to be little process and governance even in large institutions to ensure data effectiveness.
With organisations relying more and more on data, it is becoming even more prevalent to ensure data quality is high on the CIO and IT department agenda. But being high on a strategic agenda and managing the challenge effectively are not right now in unison.
I am appalled with the haphazard nature that most companies treat their second most prized resource: data (people being the first).
Commonly data input lacks standardisation and more importantly basic quality checks and controls. The number one rule in data management is 'garbage in garbage out'. Many companies engage in expensive and extensive data warehouse, business intelligence and data consolidation initiatives to 'fix' data challenges.
This is a very common and costly mistake. While these tools can certainly help you negotiate and take advantage of your data, they will not be effective if your data sources are inconsistent and lack quality controls.
In active and growing organisations, creating a data model is a must. Many people don't do it because information always seems to be a moving target in that sources are added, removed and changed often - in some cases on a daily basis.
Yet this is the very reason why having a comprehensive data model is essential. The model allows you to plot and understand the significance of changes in your data and data sources as it relates to other data and information.
Another important piece of the puzzle is having a data governance process - essentially a change control procedure for data. Usually this means setting up a board or group of stakeholders that establish the data guidelines and sign off on how the data will be handled within the greater information architecture.
Data needs to be validated and needs to account for itself through checks and balances, especially where financial or sales information is concerned. This can often be difficult as the relationship between data aspects in organisations can be very vague.
Part of the importance of data governance is to ensure that the founding assumptions and integrity of data as it relates to information is not compromised.
Do yourself a favour: establish a data model and introduce data governance and let's see if we can't improve the impact of this vital company resource.
Make sure you not only identify data management as a key strategic and operation focus in your organisation but also educate your company as to why data issues occur. Implement and champion key standards and quality controls at point of entry or where source data is obtained.
One of the great things about doing this right is you can easily quantify the impact that managing better data has in your organisation.
Stop blaming other people for bad data and lead the charge to rid your organisation of data that is meaningless - and allow information to become the heart and soul of your organisation.
Comments
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1. Ron Livesey
Too often I have witnessed the direct results of poor and inaccurate data provided without context only compounds the challenges.
Often this results in data and information management in 'organic' systems i.e. the first, prime and most expensive of resources of any organisation; people.
I agree, create models, provide context that data dimensionality can be extended, understood and leveraged, but also provide the tools for its navigation and use to those that gather it.