Tag: Olap
What Are the Differences Between OLTP and OLAP?
Confused by online transaction processing (OLTP) and online analytical processing (OLAP) in the world of databases? Fear not. We have a simple explanation right here.
To understand the differences between OLTP and OLAP, we first need to understand where they fit into the world of data and databases. And the answer is “data warehousing”.
A data warehouse is a system used for reporting and data analysis. They are central repositories of data from one or more disparate sources, including relational databases.
A Subscription Business Data Model
In the previous two parts, we’ve presented the live database model for a subscription-based business and a data warehouse (DWH) we could use for reporting. While it’s obvious that they should work together, there was no connection between these two models. Today, we’ll take that next step and write the code to transfer data from the live database into our DWH.
The Data Models Before we dive into the code, let’s remind ourselves of the two models we’ll work with.
A Subscription Business Data Model
Can you design an OLAP database model from an OLTP model? In this article, we’ll show you how! This is the second article of our data warehouse (DWH) series. You can find the first one here. The idea behind the series is to start with the OLTP (Online Transaction Processing) database model, present a possible solution for the reporting/OLAP (Online Analytical Processing) data model, and then finally consider the code we’ll use to perform the ETL process.
A Subscription Business Data Model
Welcome to a new series that shows you the practical side of the data warehouse (DWH)! In the first article, we’ll tackle a data model for a subscription business.
In previous data warehouse articles (The Star Schema, The Snowflake Schema, Star Schema vs. Snowflake Schema) we focused more on the theory. In this series, we’ll show you how you could create a data warehouse for a real-life application, such as a database model.
The Star Schema
Today, reports and analytics are almost as important as core business. Reports can be built out of your live data; often this approach will do the trick for small- and medium-sized companies without lots of data. But when things get bigger – or the amount of data starts increasing dramatically – it’s time to think about separating your operational and reporting systems. Before we tackle basic data modeling, we need some background on the systems involved.
13 Blog Articles on Database Design Best Practices and Tips
There’s a lot to keep in mind when you’re designing a database, and very few of us can remember every valuable tip and trick we’ve learned. So, let’s take a look at some online resources that feature database design tips and best practices. As we go, I’ll share my own opinions on the ideas presented, based on my experience in database design. Obviously, this article is not an exhaustive list, but I’ve tried to review and comment on a cross section of sources.
Spider Schema – a Bridge Between OLTP and OLAP?
Introduction As I mentioned in my article “OLAP for OLTP practitioners”, I am working on a project that needs to create an analytical database for on-line analytical processing (OLAP). I have mostly worked with on-line transaction processing (OLTP) with some limited reporting features. OLAP is a new area for me. In OLAP, the main focus of the database itself is simply to store data for analysis; there is limited maintenance of data.
OLAP for OLTP Practitioners
I am currently working on a project where we need to create a database that will be primarily used to store data for reporting and forecasting. In the past, I have mostly worked with databases used for typical CRUD (create, retrieve, update, and delete) operations of data with some limited reporting features. When performing CRUD operations, normalization is important; while in analytics, a de-normalized structure is generally preferred.
