Have you finished preparing your logical data model in Vertabelo? Awesome! In this article, we'll show you how to generate the physical data model from the logical model in Vertabelo. It’s just a few clicks away. Ready? Let's dive into it. Quick Intro In this article, we'll deal with a slightly modified version of Microsoft's Northwind Database. We often use it in our LearnSQL courses, such as Customer Behavior Analysis in SQL.
Amazon Redshift is one of the most popular cloud databases. Could it be your data-warehouse solution? Read on to find out if Amazon Redshift meets your needs. In 2012, Amazon announced its new cloud database system called Redshift. Basically, it is a data-warehouse solution intended for analytical systems, which can handle huge volumes of data—up to 1 petabyte (1024 TB). Amazon Redshift is available as a service (Database as a Service) and is a part of a bigger cloud ecosystem called Amazon Web Services (AWS).
Find out how to create logical data models in Vertabelo! If you have some experience with physical diagrams, this will be as easy as pie. There are three different levels of data models: conceptual, logical, and physical. Of these, the conceptual model is the most abstract, and the logical model has a few more technical details. The physical model has all the details of the physical database, such as data types (integer, decimal, money, varchar, etc.
There are many online portals which allow investors to lend money directly to individual borrowers – with no banks acting as intermediaries. What data model might underlie such a site? Online lending platforms bring borrowers and investors together and allow them to choose to whom they want to lend their money (in the case of investors) and who they want to borrow money from (in the case of borrowers). Some peer-to-peer lending sites also allow borrowers and investors to make their own deals in terms of lending rates (i.
Do you dream of running a marathon? Let’s look at the data model for an app that could take you from lazy couch potato to marathoner. What do you need to run a marathon? You’ll need enthusiasm and determination. A good pair of running shoes. And lots of physical training! Let’s say you have an app that helps you go from novice runner to marathon finisher. What would the data model look like?
Board games like dominoes are still very popular. Let’s take a look at dominoes from a data modeling point of view. The game of dominoes has been around for hundreds of years, and it’s played all over the world. As you might expect, this means a lot of variations in play! In this article, we’re going to examine a data model that could support the most common variants – draw and block.
Various apps promise to make your search for parking painless. Let’s examine this type of app using our data modeling glasses. What does the underlying model look like? In an earlier article, we explained how a parking lot is structured and how a data model can be designed to manage one. In this article, we are examining the data model for a parking app. You know these apps: they list nearby parking options, tell you the prices, and let you book or reserve a space or buy a parking pass.
Lots of people use mobile weather apps to plan their day – or at least decide if they need to carry an umbrella! What sort of data model lies underneath these popular programs? We all want to know how nasty the weather is before we step outside. Windows, iOS, and Android apps give us accurate and reliable information about current weather conditions. This article explains a detailed data model that could be used for such apps.
Research shows that cars remain parked for 95% of their lifetime, suggesting that parking lot management systems should be smart, efficient, and robust. In this article, we’ll construct a data model for such a system. Introduction Before we begin constructing our data model, we should first understand how parking lots are structured and how they operate. Let’s take a brief look at these two key areas. How are parking lots structured?
Keeping up with the latest changes in technology is necessary if you want to get ahead in today’s competitive job market. In this article, we’ll build a data model for online portals that offer a more engaging platform for learning new skills, using Native Monks as our guide. Introduction In one of our recent articles, we built a working data model for an e-learning portal, and we explained how courses can be split into recorded/transcript lessons and made available to students.