Technical Terms
Technical Terms Glossaryπ
This glossary provides simple explanations of some technical terms used by the Data Intelligence team.
Aπ
Azure SQLπ
Azure SQL is a cloud-based database service from Microsoft that lets businesses store, manage and access their data over the internet.
Bπ
Backendπ
In the context of web and software development, the backend refers to the part of a system that users don't see. Itβs responsible for managing data, application logic and server-side functionality. If you think of a restaurant, the backend is like the kitchen where all the cooking happens, while the front end is the dining area where customers enjoy their meals.
Cπ
Cloud Servicesπ
Cloud services refer to computing resourcesβsuch as storage, servers, databases, networking, and softwareβthat are delivered over the internet instead of being hosted on local computers or physical data centers. n simple terms, instead of buying and maintaining your own hardware, you "rent" resources from cloud providers like AWS, Microsoft Azure, or Google Cloud.
CSVπ
A Comma-Separated Values (CSV) file is like a big list of things written in a notebook. A CSV file does the same thing on a computer! It keeps information in a simple way, using commas (,) to separate things.
Dπ
DaaSπ
Data-as-a-Service (DaaS) is a business model where data is made available on cloud infrastructure on demand and regardless of the consumerβs location or infrastructure through the internet.
Eπ
ETLπ
Extract, Transform, Load (ETL) is a computing process to get, retreive, extract information. Then transform, change and modify the information to meet the requirements of the data warehouse and then load, upload and insert the data into the data warehouse.
Fπ
Gπ
Hπ
Iπ
Jπ
JSONπ
JSON (JavaScript Object Notation) is a lightweight data format that is easy for humans to read and write, and easy for machines to parse and generate. A really basic example of JSON looks like this:
Kπ
Lπ
Legacy Softwareπ
Old, obsolete, out of date software needing replacement.
Mπ
Nπ
Oπ
Pπ
Qπ
Rπ
RDBMSπ
Relational Database Management System (RDBMS) is a type of database management system that stores data in a structured data format using rows and columns.
Sπ
SaaSπ
Software-as-a-Service (SaaS) is a business model in which applications on cloud infrastructure are made available on demand and regardless of the consumer's location or infrastructure through the internet.
Scale outπ
Scaling out is adding more machines to the infrastructure to spread the load.
Scale upπ
Scaling up infrastructure is adding more computing resources to a machine.
Semi Structured Dataπ
This data has some structure, but it's not as rigid as a table. There are patterns, but they donβt have to fit into fixed rows and columns. This is more flexible than structured data but still somewhat searchable (think JSON files).
SQLπ
Structured Query Language (SQL) is a programming language used to manage and manipulate relational database management systems (RDBMS).
An example of a simple SQL query is:
SSISπ
SQL Server Integration Services (SSIS) is a propriety tool owned by Microsoft to write, deploy and run ETL processes. SQL Server Integration Services is a platform for building enterprise-level data integration and data transformations solutions.
Structured Dataπ
This is data thatβs highly organized and stored in tables with rows and columns. Every piece of data fits perfectly into a specific place. It's easy to search and analyse because everything is in a fixed format.
Tπ
T-SQLπ
Transact-Structured Query Language (T-SQL) is Microsoft's propriety language to manage databases, query data and add procedural programming into the a database.
Uπ
Unstructured Dataπ
This is data with no fixed formatβit can be anything from text to images, videos, or emails. It doesnβt fit neatly into tables.
Vπ
Wπ
Xπ
XLSXπ
XLSX is a file format used by Microsoft Excel to store spreadsheets. It's like a super smart notebook on a computer. It has fancier features than a CSV file such as colours, formulas and even pictures.