Data Quality

  • Easy
  • 40 min

In the IT world, the data is everywhere. It could be recorded in databases, both relational and NoSQL. It could be also data in streams and message queues; as well as files in local, distributed and cloud filesystems. The data is prepared by people and by computer programs. The consumers could be both people and computer programs as well. Basing on the data some forecasts and plan budgets and actions for the future. 

Now, imagine that at the earlier beginning there was an error in data, for instance, the data has been corrupted, incomplete or inconsistent. Even a small data issue can grow like a snowball and turn into a big problem at the end of data transformation. It could lead to absolutely wrong decisions. 

 Let's look at methods that can help to be confident about both input and output data which is used in our system.

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