Long ago I read an article about an apparently strange behavior: if you’re seeing a person looking at their watch and you immediately ask what time it is, just a small percentage can tell you the correct time. Some researches tried to investigate what’s the explanation for this apparently strange behavior. The results were quite

Shift left testing is an approach to Data Warehouse (DW) / BI development where testing is performed early in the lifecycle. Shifting left refers not only to dynamic data and BI application testing- it also refers to static testing, conducting reviews and inspections, and even more unit and integration testing. In this article, we highlight:

What better way to start this new century than to go over the pros and cons of the 4th Industrial Revolution. The 4th industrial revolution is a term coined by Professor Klaus Schwab. He is the founder and Executive chairman of the World Economic Forum, so he has some good credentials. He described the 4th

I think that sometimes people still struggle to understand what data governance is. That’s why, when I’m talking about data governance I like to first make a reference to HR and Finance. This is usually when I’m asked what I do for work, what do I speak at conferences about, what do I create videos

You probably use checklists to record and efficiently execute a wide range of daily work tasks. But if you don’t use data warehouse testing checklists for developing and monitoring your data warehouse quality assurance (QA), you’re missing an enormous boost in productivity and proficiency. Procedural data warehouse checklists serve as concrete reminders of which jobs

We are approaching winter, the days are shorter but IT’s always there, running everywhere in your mind, including at night between two dreams: Master Data Management (MDM)! For some time now, your company is working to be data-driven and your evolution in this field has made you understand that you have to go this way:

Today’s Data Warehoues (DW) source data often originates from a large variety of data formats as illustrated in Figure 1. Original sources may consist of external data, reference data, business transactions, production raw data and more. The multitude of data sources each has its own methods, systems, and architectures for storing data. When working with

When you’re setting up a data stewardship program, you need to start thinking of not only who to assign as data stewards and the operational framework, but also who the data stewards should report to, from a data governance organization perspective. The role of the data steward is usually not a new position that is

Effective Data Warehoues (DW) data source profiling is often an overlooked step in data warehouse data preparation. DW project teams need to understand all quality aspects of source data before preparation for downstream consumption. Beyond simple visual examination, you need to profile, visualize, detect outliers, and find null values and other junk data in your

This quick guide provides an overview of the basic concepts in fault tree analysis technique, as it applies to data quality. For some more well-known and useful root cause analysis techniques, please check out the: 5 whys analysis Fishbone diagram Barrier analysis Pareto analysis Definition The fault tree analysis is a top-down, deductive failure analysis