Choosing the best Oracle database design tool can be the difference between a streamlined database design process and a complex, frustrating one. Dive deep into this comparative analysis of the top Oracle database modeling tools, from their collaboration capabilities to their model validation strengths. In the complex ecosystem of Oracle, having the right database design tools can dramatically improve workflows and results. Whether you're diving into ERD software or seeking a visual database design tool for Oracle, knowing the features and strengths of each option is crucial.
Want to find out about the role of data engineers and data engineering? What are the top data engineering tools these professionals use? Read on to explore more. Data engineers create pipelines to facilitate an organization's data analytics by collecting, merging, and transforming data. They create an infrastructure for modern data analytics. Data engineers' work can be categorized into various sets of requirements that they must fulfill in building the pipeline.
Want to start your next Oracle database project? Find out the best Oracle ER diagram tool and save yourself some time and extra work! Oracle is one of the best and most popular database management systems (DBMSs) in the world. Many database architects prefer to use Oracle because of its easy networking and interaction, cross-platform service, simple administration and maintenance, and other benefits. On the other hand, an ER diagram (entity-relationship diagram) is an essential tool for data modeling.
When you’re using a data warehouse, some actions get repeated over and over. We will take a look at four common algorithms used to deal with these situations. Most DWH (data warehouse) systems today are on a RDBMS (relational database management system) platform. These databases (Oracle, DB2, or Microsoft SQL Server) are widely used, easy to work with, and mature – a very important thing to bear in mind when choosing a platform.
Having reference tables in your database is no big deal, right? You just need to tie a code or ID with a description for each reference type. But what if you literally have dozens and dozens of reference tables? Is there an alternative to the one-table-per-type approach? Read on to discover a generic and extensible database design for handling all your reference data. This unusual-looking diagram is a bird’s-eye view of a logical data model (LDM) containing all the reference types for an enterprise system.
In the 3rd post in this series, we looked at how we prepare data for use with a concept called the Business Data Vault. Now, in this final part, I will show you the basics of how we project the Business Vault and Raw DV tables into star schemas which form the basis for our Information Marts. Raw Data Mart vs. Information Marts As of Data Vault 2.0, the terminology changed a bit to be more precise.
In my last post, we looked at the need for an Agile Data Engineering solution, issues with some of the current data warehouse modeling approaches, the history of data modeling in general, and Data Vault specifically. This time we get into the technical details of what the Data Vault Model looks like and how you build one. For my examples I will be using a simply Human Resources (HR) type model that most people should relate to (even if you have never worked with an HR model).
Why Talk About Errors? Model Setup 1 – Using Invalid Names 2 – Insufficient Column Width 3 – Not Indexing Properly 4 – Not Considering Possible Volume or Traffic 5 – Ignoring Time Zones 6 – Missing Audit Trail 7 – Ignoring Collation Why Talk About Errors? The art of designing a good database is like swimming. It is relatively easy to start and difficult to master.
The Vertabelo journey continues … We now have almost 10,000 users and the number of Vertabelo advocates keeps growing strong. Vertabelo users come from over 100 countries and speak various languages. What unites them? The relational database. Let’s see what relational databases they use: We wanted to determine the most popular database engine among Vertabelo users based on one of three widely-used operating systems: Windows, Linux, Mac OS.
When looking at different kinds of ERD notations, it is hard not to come across Barker’s ERD notation, which is commonly used to describe data for Oracle. Richard Barker and his coworkers developed this ERD notation while working at the British consulting firm CACI around 1981, and when Barker joined Oracle, his notation was adopted. Let’s take a closer look at Barker’s syntax. The most important components in the ERD diagram are:
Some time ago, the Vertabelo Team participated in the PostgreSQL Conference Europe 2013. Some of the talks were really nice. One of them stuck in my head for quite a long time. It was Markus Winand’s lecture titled “Indexes: The neglected performance all-rounder.” Although I had had a solid background in databases, this 50 minutes long talk showed me that not everything concerning indexes was as clear to me as I had thought.