June 9th, 2008
Excuse me for going a little off topic but Data Integrity is essential to even the most rudimentary Information Visualizations.
No visualization is worth a thing if it leads you to the wrong conclusion.
Often, as new and interesting terms arise in the IT industry (buzz words), they are carelessly tossed around in the attempts to impress (and often confuse) the intended audience.
buzz.word n. — A usually important-sounding word or phrase used primarily to impress laypersons.
More often than not, I notice people have varying perceptions of what such terms actually mean, causing a barrier to clear communication.
Here’s what I imagine people thinking as they are subjected to jargon/buzzwords:
“What does your flashy new term really mean?”
“Should I be impressed that it’s a word or term I’ve never heard before?”
“I’d much rather you explained it in a way that actually meant something to me.”
What does Data Integrity really mean and why is it an important term for people to understand?
As the need to derive meaningful information from large sets of data becomes a higher priority both in the government and private sector, Data Integrity is what gives users the assurance that the information they see is trustworthy.
Many organizations build and rely on a Data Warehouse,
“…the main repository of an organization’s historical data, its corporate memory. It contains the raw material for management’s decision support system”
I believe I’ve identified a few definitions that hopefully embody what Data integrity is meant to be:
Wikipedia:
Data Integrity is a term that can mean ensuring data is “whole” or complete…
Put simply, data integrity is the assurance that data is consistent, correct, and accessible.
In relation to data warehousing projects, where data integrity efforts have significant and widespread impact:
The author of Ensuring Data Integrity offers:
…Data Integrity is defined as information that adheres to a strict standard of value and completeness. That is, the data is both accurate and the entire population of relevant data is contained within the data warehouse.
The credibility of the data warehouse solely rests with the integrity of its data.
So, Data Integrity is clearly important and may in fact be a term that incorporates a number of niche terms relating to the proper management of data.
So, now it seems there are so many more questions…
- How does one ensure data integrity?
- How can the integrity of data be compromised?
- What activities go in to providing data integrity assurance?
- How is data integrty success/failure reported?
- What’s the worst that could happen if a little of my data lacks integrity?
I hope I have enough time to try and figure all that out…
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