Cameras, revolving doors, elevators, temperature sensors, alarms – all of these devices produce a large number of interconnected signals that are related to events happening around us. Now imagine you’re the person who needs to track statuses, produce real-time reports, and make predictions based on all this signal data. To do this, you’d first need to store that data. A data model that supports such signal processing is the topic of today’s article.
What data model would allow you to comfortably search for books and borrow them in your local library? Have you ever gone to a library and borrowed a book? Maybe that seems old-fashioned in today's world of instant internet knowledge and e-books. But I'm sure there's still this analog part of you that still likes to smell, touch, and read books. Or maybe you were forced to use a library when you couldn't find something on the internet!
Everybody books into a hotel at some point. In this article, we’ll look at a data model that could power a hotel reservations system and channel manager. Faster, cheaper transportation options allow us to travel across the world in a matter of hours. And people have more disposable income than ever before. Is it any surprise that tourism is growing rapidly? In addition to traditional hotel booking channels, we also have newer options – like Airbnb and Booking.
In the previous two articles of this series, we discussed how to use Python and SQLAlchemy to perform the ETL process. Today we’ll do the same, but this time using Python and SQL Alchemy without SQL commands in textual format. This will enable us to use SQLAlchemy regardless of the database engine we’re connected to. So, let’s start. Today we’ll discuss how to perform the ETL process using Python and SQLAlchemy.
SQLAlchemy helps you work with databases in Python. In this post, we tell you everything you need to know to get started with this module. In the previous article, we talked about how to use Python in the ETL process. We focused on getting the job done by executing stored procedures and SQL queries. In this article and the next, we’ll use a different approach. Instead of writing SQL code, we’ll use the SQLAlchemy toolkit.
Python is very popular these days. Since Python is a general-purpose programming language, it can also be used to perform the Extract, Transform, Load (ETL) process. Different ETL modules are available, but today we’ll stick with the combination of Python and MySQL. We’ll use Python to invoke stored procedures and prepare and execute SQL statements. We’ll use two similar-but-different approaches. First, we’ll invoke stored procedures that will do the whole job, and after that we’ll analyze how we could do the same process without stored procedures by using MySQL code in Python.
Do you want to learn how to design a database system and map a business process to a data model? Then this post is for you. In this article, you’ll see how to design a simple database schema for a recruitment company. After reading this tutorial, you will be able to understand how database schemas are designed for real-world applications. The Recruitment System Business Process Before designing any database or data model, it is imperative to understand the basic business process for that system.
SaaS (Software as a Service) is one of the three main components of Cloud computing. Usually, SaaS applications are web-based and can handle many different users at one time. Subscription-based solutions are very popular SaaS offerings. Some well-known SaaS products include Microsoft Office 365, Amazon Web Services (AWS), Slack, Jira, Stripe, and (of course) Vertabelo! Today we’ll take a look at a data model that would allow us to manage SaaS subscriptions.
Are you forgetting something? A data model to help you remember important dates – before they happen. Have you ever forgotten an important date – your mom’s birthday or your anniversary? Or that you’re giving a lecture? Yup, things like that happen in real life. Maybe not to all of us, but to some of us (including me), they certainly do. To prevent such disasters, we’ll create a data model you could use as the background for an application that will notify you right on time.
Producing a great wine is a really complex process, one that takes many years to master. Offering and selling wines to customers is another complicated process. There are many stores specializing in only one product. If you want that product, you’ll go to that store. Wine stores are an example of what I’m talking about. What would be the data background of a wine store? Let’s find out.In many ways, a wine store is like any other store. So, you can expect this data model to have most of the tables common to any other retail business. Still, there will be some details that will distinguish this model from others.
Running an automobile/car repair shop is a really complex business. You’ll need to make appointments while some customers will drive in and you don’t want to have them wait for hours. Also, you’ll need to organize employees, track repairs, materials, charge customers, etc. You’ll definitely need an IT solution and, of course, a data model in the background. Today we’ll talk about one such model.The IdeaI’ve already mentioned that this business model is really complex. Therefore, I won’t try to cover everything. I’ve intentionally omitted tracking materials and spare parts and also simplified some parts of the model. The reason for that is pretty simple. If I’ve included really everything, the model would simply be too large for an article of the reasonable size. So, let’s start.
Smart homes used to be strictly in the future; now they are a reality. Most of us have heard about them, but they are not so widespread as they will be in the near future. Managing your home the ‘smart’ way will definitely produce a lot of data. Today, we’ll analyze a data model we could use to store smart home data.The Data ModelWhen you think of a smart home, you probably think of remotely locking and unlocking your home, activating alarms, lights, or cameras from your phone, having thermometers that automatically manage your heating and cooling, etc. But smart homes can do much more. You can connect a number of smart devices and controllers to achieve many complex functionalities. You can send instructions to devices or read their statuses from wherever you are.
Freelancing is becoming more and more popular these days. While most freelancers are a one-man band, that’s not the only option. You could be a part of a collective and collaborate on larger and more complex projects. A data model that could power a freelancers collective’s app is the topic of today’s article.Freelancing is not new, but it’s becoming more and more popular. Working from 9:00 to 17:00 has certain advantages, but it also comes with many disadvantages. Therefore, an increasing number of people decide to become freelancers.
You’ve probably made some of these mistakes when you were starting your database design career. Maybe you’re still making them, or you’ll make some in the future. We can’t go back in time and help you undo your errors, but we can save you from some future (or present) headaches.Reading this article might save you many hours spent fixing design and code problems, so let’s dive in. I’ve split the list of errors into two main groups: those that are
What is needed to produce electricity? We look at a data model that can organize the power production process.In the electric power distribution system article , we discussed a data model for an electric power distribution system. We focused on how the electricity was provided to customers via the transmission grid and the local transmission grid. Due to space constraints, we treated the production process as a black box. Today, we’ll look inside this black box, discussing what kind of model could store details about electrical production facilities, owners, energy produced, and related costs.
Have you ever wondered how electricity gets from the power station to your home or office? In this article, we’ll look at a database model that could work for an electricity distribution system.Electricity is so widespread that we can hardly imagine life without it. The first hydroelectric power station may have been built back in 1868, but there are still plenty of innovations going on with electricity. The most attention-getting are electric cars, like Teslas or Rimacs. Other inventions may not be so shiny, but they provide serious improvements in transporting electricity (new conductor types, superconductors) and storing it (new battery types with greater capacity).
The process of defining your data warehousing system (DWH) has started. You’ve outlined the relevant dimension tables, which tie to the business requirements. These tables definewhatwe weigh, observe and scale. Now we need to definehowwe measure.Fact tables are where we store these measurements. They hold business data that can be aggregated across dimension combinations. But the fact is that fact tables are not so easily described – they have flavors of their own. In this article, we’ll answer some basic questions about fact tables, and examine the pros and cons of each type.
In my last post, I wrote about ensuring that your data model properly handles global information : numbers, currencies, phone numbers, addresses, dates, and time zones, among other things. However, I’ve realized that many example data models have exactly the “self-centric” or “Amero-centric” approach that I cautioned against.As an American living abroad (for almost 30 years now), I often find that people make too many assumptions about the universality of what they know. For example, some Americans assume that others automatically understand their country’s ZIP code system, and its supplementary ZIP+4 version. In my experience, most of the world has no idea what a ZIP+4 is.