Data quality - Where to start ?

Less poor data is essential

Data quality is about making sure that data are accurate and coherent.

What type of organization, big or small, can say that they're not concerned by data quality ? None, of course. 

Many different types of data are collected (for research, transactions, customer or administrative care, demographics, social media activity, surveys, basically all informations aimed at statistics...).

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Distilling your data into valuable information

Analogy between a whisky distillery and data management

The similitudes don't typically jump out, do they? But you'll quickly see the point. 

On one side, in a whisky distillery we have engineers who build the tubings and alembics and such (the containers), and biologists who are in charge of taking care of the many processes leading to the final product (the content). It's all about measuring the quality and tasting.

Once bottled, the blend of whisky goes to meet the world (and be enjoyed by happy consumers).

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Data quality : when do you have too much data ?

Our cavemen ancestors were all about foraging. Times were tough and to survive one needed to go hunt or search for plants. We've come a long way since then of course, but a small part of us still reacts pretty much the same way. We consider accumulation as a richess. But what is true for more traditional assets such as gold is not necessarily true for modern business assets such as data.

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