More than ever, the ability to use data for decision-making is critical to company success. Despite this knowledge, companies are still not fully empowering their employees with easy access to the data they need. According to Zhamak Dehghani, the founder of Data Mesh, we must start thinking outside of the box because the traditional approach…
I recently completed a project where we modeled business processes for the Surveying and Mapping Authority in Slovenia and I co-authored and presented a paper about it at the Slovenian Society Informatika annual conference in April 2019. Some of the main benefits of this project that we outlined in the paper were: Business process modeling…
The new general EU Data Protection Regulation (GDPR) will become a binding law at end of May this year. The aim of the regulation is to establish greater control over the handling of personal data. As project managers, we must be aware that personal data may also be handled within projects, especially with respect to…
Recently, I was approached by a colleague who is preparing to take the PMI Agile Certified Practitioner (PMI-ACP) to share my experience. It has been almost 5 years since I passed the exam and I would probably have forgotten many of the details, were it not for this article that I wrote for the…
Agile software development is most often associated with small companies and small development teams. The very fact that agile teams should have no more than about a dozen members sets limitations that lead us to question the possibility of doing large enterprise data warehousing projects in an agile manner. Despite the limitations, agile can nevertheless…
Ever since Ralph Kimball, the guru of dimensional modeling, announced his retirement, it has felt like the end of an era. He was among the first data warehousing/business intelligence pioneers some 20 years ago and although there has been much advancement in the field since then, his dimensional modeling principles are still strongly rooted and…
Relational databases introduced data modeling concepts where we represent a data model with tables, fields and relationships. A new generation of NoSQL databases which are more suitable for big data environments no longer rely on relational data models. We have to think about data modeling in a different way, primarily to ensure that data is…
In data warehousing and business intelligence implementations we usually start by choosing between two most popular approaches. One of them is the enterprise normalized data warehouse approach as defined by Bill Inmon, the father of data warehousing. The second approach is a collection of dimensional data marts based on a common bus architecture as popularized…
Loading data into data warehouses, also known as the ETL process, is an established way of taking data from the source systems and bringing it into the data warehouse. The process consists of three steps: Extract data from the source systems, Transform the data so that it conforms to the data warehousing environment and finally Load…
When we talk about Big Data, we nearly always associate Hadoop as the platform for storing huge amounts of data in a distributed environment. We often include MapReduce as the programming model for processing large data sets. Although it has been known for some time that MapReduce has limitations and is thus not universally applicable…