Author: Gustavo du Mortier
Gustavo du Mortier is a functional and data analyst at MasterSoft, an Argentinean software company specializing in ERP and healthcare solutions. He’s written many books and articles on different aspects of programming and databases. In his spare time, he plays guitar and helps his two sons build and enhance their gaming computers.
How to Model for Easy Database Maintenance
You may think database maintenance is none of your business. But if you design your models proactively, you get databases that make life easier for those who have to maintain them.
A good database design requires proactivity, a well-regarded quality in any work environment. In case you are unfamiliar with the term, proactivity is the ability to anticipate problems and have solutions ready when problems occur – or better yet, plan and act so that problems don’t occur in the first place.
7 Tips for Staying Relevant as a Data Modeler
Many people draw boxes connected by lines and think they do data modeling. But we data modelers know our work goes far beyond that. Here are the desired skills in data modeling and important considerations for staying relevant as a data modeler.
Data modelers are essential in many situations. We are called to be part of a software development team in the early stages of a project for building the foundations of a software solution.
What I Like About Database Modeling
The greatest satisfaction of database modelers is in seeing their creations transformed into efficient repositories of information for business processes. Of course, modeling databases can also have its share of frustrations, but we'll get to that.
What makes building scale models fun? Whether it’s RC cars, airplanes, ships, or a science-fiction spacecraft, scale models allow you to build a miniature representation of huge real-life objects.
I was fascinated by scale models when I was a kid.
What Are Facts and Dimensions in a Data Warehouse?
Facts and dimensions are the fundamental elements that define a data warehouse. They record relevant events of a subject or functional area (facts) and the characteristics that define them (dimensions).
Data warehouses are data storage and retrieval systems (i.e., databases) specifically designed to support business intelligence (BI) and OLAP (online analytical processing) activities. They are different from databases designed to support transactional systems – e.g., e-commerce sites – whose function is primarily OLTP (online transactional processing).
The Best Data Modeling Books
Most of the best books on data modeling were originally written decades ago. But the concepts they discuss are more relevant than ever; in today’s business world, most decisions are made on the basis of well-modeled data repositories.
With the rise of NoSQL databases, unstructured information, and Big Data repositories (where quantity seems to be more important than quality), you might think that data modeling is an archaic discipline. That notion can be maintained until inconsistent data, anomalies, and inaccurate reports start to pop up everywhere and you begin losing confidence in your data.
How to Document Design Decisions in Database Modeling
Sometimes your data models speak for themselves. But for those who don’t understand their language, you need to add clarifications that explain the reasons behind your design decisions.
You may think that your database designs are works of art and therefore need no explanation. But the problem with works of art is that each person who looks at them can interpret them differently. This is fine from an artistic point of view, but it doesn’t work in day-to-day database work.
The Benefits of Data Modeling
Don’t put off until tomorrow what you can model today. Every minute you spend building and keeping your data model up to date means hours saved in the future.
In my early days as a database designer, I thought data modeling was an unnecessary step that only delayed the time to get the databases up and running. I thought that because, in most cases, databases started with just a few entities – 6 or 7, tops.
How to Become a Database Designer
Database modeling has some science, some art, a lot of techniques, and quite a bit of general wisdom. All good database modelers study a lot, practice a lot, cultivate creativity, and develop interpersonal skills.
The road to becoming a database designer may seem arduous. But if you enjoy working with data, giving structure where there seemingly is none, and helping people find hidden truths in tides of information, you will definitely find the journey enjoyable.
Database Design for Audit Logging
Thinking of a database design for audit logging? Remember what happened to Hansel and Gretel: they thought leaving a simple trail of breadcrumbs was a good way to trace their steps.
When we design a data model, we are trained to apply the philosophy that now is all that exists. For example, if we design a schema to store prices for a product catalog, we may think that the database only needs to tell us the price of each product at the present moment.
Database Tools You Need to Work Effectively
Think of them as your sidekicks to deal with the challenges you encounter every day in working with databases.
Good database tools come to the rescue in all stages of the database lifecycle: from the conceptual design, through logical/physical design, all the way to maintenance, refactoring, and optimization.
Every database professional, be it an architect, engineer, designer, programmer, tester, or administrator, has a preferred set of tools. Some tools are specific to the database system (RDBMS), such as MySQL, Oracle, SQL Server, or PostgreSQL, while others work with virtually any database engine.
