If I enjoy a restaurant meal it is basically unimportant to me what raw ingredients from where were used and which tools the chef used during preparing the meal. My concerns are whether the taste meet my expectations, the plate looks delicious in my eyes, the waiter seems nice and so on.
This is comparable to when we talk about information quality. The raw data quality and the tools available for exposing the data as tasty information in a given context is basically not important to the information consumer.
But in the daily work you and I may be the information chef. In that position we have to be very much concerned about the raw data quality and the tools available for what may be similar to rinsing, slicing, mixing and boiling food.
Let’s look at some analogies.
Fresh raw ingredients is similar to actualized raw data. Raw data also has a best before date depending on the nature of the data. Raw data older than that date may be spiced up but will eventually make bad tasting information.
Buying all your raw ingredients and tools for preparing food – or taking the shortcut with ready made cookie cutting stuff – from a huge supermarket is fast and easy (and then never mind the basket usually also is filled with a lot of other products not on the shopping list).
A good chef always selects the raw ingredients from the best specialized suppliers and uses what he consider the most professional tools in the preparing process.
Making information from raw data has the same options.
Governments around the world has for long time implemented regulations and inspection regarding food mainly focused at receiving, handling and storing raw ingredients.
The same is now going on regarding data. Regulations and inspections will naturally be directed at data as it is originated, stored and handled.
Have you ever tried to prepare your favorite national meal in a foreign country?
Many times this is not straightforward. Some raw ingredients are simply not available and even some tools may not be among the kitchen equipment.
When making information from raw data under varying international conditions you often face the same kind of challenges.