BiG EVAL - High Data Quality Mastered

No More Firedrills Guide to Business Intelligence Testing

This Free eBook shares the Experience of Data Quality Experts

eBook cover No More Firedrills Guide to Business Intelligence Testing

See how top-notch experts get business intelligence systems delivering trustful and reliable data by applying a proper testing strategy. This 5-star rated guide from the "No more firedrills" series, shows you how to automate testing, to make it more efficient and put developers out of the misery of performing poor testing tasks.

In this guide you will discover:

  • Proven Tipps and Tricks from industry experts.
  • Test cases and strategies for all business intelligence components.
  • High test-coverage strategies with less effort.

Sample Contents

Why is testing so important?

Testing is often underestimated because the subject raises some important questions. We often hear, for example, that people want to test their data warehouse "only later", or "why should I test it at all"? Or "we have built our own testing framework".
We are taking a closer look and correcting these statements.

Testing a Business Intelligence System

We use a state-of-the-art BI-architecture to show you the topic of testing. This includes components like staging area, ETL- or ELT process, data loading and data cleansing as well as data marts and analytical models.

Source Data

Loading data from different sources with different behavior and specifications, means that many things can go wrong. The eBook shows you some tactics to ensure nothing bad happens with your data.

Staging Area

A staging area is a good point to start abstracting, cleaning and transforming data by your ETL-process. But ETL-processes need the right data at the right point in time to run successfully. That's why we show you some practical ideas how to ensure that everything happens at the right time.

Data Model and Meta Data

Whether you collect and combine your data in a Kimball-based dimensional data warehouse, in an Inmon-based 3NF data warehouse or even in a data vault by Linsted, quality is king.

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