Acronyms can be a huge source of confusion for data analysts, and can present a roadblock in understanding costing precious time. They can be a great tool for summarising complicated concepts, but their value only comes about if you actually know them.

In the unending search for efficiency, it seems every industry is inundated with acronyms, and the data analytics space is no exception. In our first week of training we were bombarded with a long list of them and it was then that I learned that I had a very particular skill — I know a LOT of acronyms.

Having said that, in compiling this list with the help of some of my colleagues, there were a lot that were a mystery to me. Worse still, I couldn’t find a comprehensive list that was geared towards data analysts specifically, covering the gamut of different roles we cover. With this in mind I set out to put together the most complete list possible to fill this need.

Below you’ll find 101 of the most import acronyms for a data analyst to know, in my opinion. However, I’m certain that there are some missing so if you come across one that you don’t see here, please reach out and let me know (LinkedIn, Twitter, Website)! My hope is that this list can serve as a living directory that you can refer to when you’re just a little too embarrassed to ask — I’ve got your back.

Business

3DM–Data Driven Decision Making
AP/AR–Accounts Payable/Receivable
B2B/B2C–Business-to-Business/Business-to-Consumer
BEP–Break-even Point
BI–Business Intelligence
CAGR–Compound Annual Growth Rate
CEO/COO/CDO/CRO/CMO etc.–Chief Executive Officer/Chief Operating Officer/Chief Data Officer
CLV–Customer Lifetime Value
COB/EOD–Close of Business/End of Day
CRM–Customer Relationship Management
ERP–Enterprise Resource Planning
ESG/CSR–Environmental Social Governance/Corporate Social Responsibility
KPI–Key Performance Indicator
MVP–Minimum Viable Product
ROI–Return on Investment
SKU–Stock Keeping Unit
SLA–Service Level Agreement
SMA/EMA–Simple/Exponential Moving Average
SMB–Small-Medium Business
SME–Subject Matter Expert or Small-Medium Enterprise
SWOT–Strengths Weaknesses Opportunities Threats
TTV–Time To Value

Consulting

MECE–Mutually Exclusive and Collectively Exhaustive
MSCW (MoSCoW)–Must-have/Should-have/Could-have/Wont-have
OTB–On The Beach/Bench
PM–Project/Product Manager
RFP/RFQ–Request For Proposal/Request for Quote

Databases

ACID–Atomicity, Consistency, Isolation, Durability
CRUD–Create, Read, Update, Delete
DBA–Database Administrator
DDL–Data Definition Language
DML–Data Manipulation Language
ETL/ELT–Extract Transform Load/Extract Load Transform
MDM–Master Data Management
NoSQL–No SQL/ Not Only SQL
ODBC–Open Database Connection
ORM–Object Resource Mapper
R/DBMS–(Relational) Database Management System
SQL–Structured Query Language

Data Types/Languages

CSV/TSV/PSV–Comma/Tab/Pipe Separated Values
DAX–Data Analysis Expressions
JSON–JavaScript Object Notation
RE/RegEx–Regular Expressions
VBA–Visual Basic for Applications
XML–Extensible Markup Language

General

AI/ML–Artificial Intelligence/Machine Learning
CV–Curriculum Vitae
EDA–Exploratory Data Analysis
JIAL–John Is A Legend
KISS–Keep It Simple Stupid
MoM/YoY–Month on Month/Year on Year
PSMAT–Please See Me About This
SMART–Specific Measurable Achievable Relevant TIme-bound
TLA–Three Letter Acronym
UI/UX–User Interface/Experience
WYSIWYG–What You See Is What You Get
YAGNI–You Ain’t Gonna Need It

Infrastructure

AWS–Amazon Web Services
CDN–Content Delivery Network
CMS–Content Management System
CPU/GPU–Central Processing Unit/Graphics Processing Unit
IOT–Internet Of Things
OLTP/OLAP–Online Transaction Processin/Online Analytical Processing
S/FTP–Secure/File Transfer Protocol
SaaS/IaaS/PaaS/*aaS–Software/Infrastructure/Platform/* as a Service
VM–Virtual Machine

Programming

AJAX–Asynchronous JavaScript and XML
API–Application Programming Interface
CI/CD–Continuous Integration/Development
CLI–Command Line Interface
CRON–Command Run On
FIFO/LIFO–First In First Out/Last In First Out
GUI–Graphical User Interface
GUID/UUID–Globally Unique Identifier/Universally Unique Identifier
IDE–Integrated Development Environment
NLP–Natural Language Processing
OCR–Optical Character Recognition
OOP–Object Oriented Programming
OS–Operating System
QA–Quality Assurance
SCM/VCS–Source Control Management
SDK–Software Development Kit
SLC–Software Lifecycle
TDD–Test Driven Development
UAT–User Acceptance Testing

Standards

GMT–Greenwich Mean Time
ISO–International Standards Organisation
UPC–Universal Product Code
UTC–Coordinated Universal Time
UTF–Unicode Transformation Format

Web

CTA–Call To Action
CTR–Click Through Rate
DOM–Document Object Model
HTML–Hypertext Markup Language
HTTP/S–Hypertext Transfer Protocol
MAU/DAU–Monthly/Daily Active Users
PPC–Pay per Click
REST–Representational State Transfer
SEO–Search Engine Optimisation
URL/URI–Universal Resource Locator/Identifier

There you have it! 101 Data Analyst Acronyms You MUST Know (according to me)! Please let me know if you have any ideas for more data analyst acronyms I might have missed. And, keep an eye out for more of my blogs on The Data School Australia Blog for more content about data analytics, and finding my place in it.

I’ve been your host Dan Lawson, a Data Analyst (Trainee) from the mighty Cohort 17, and you can find out more about me on my personal blog at https://danlsn.com.au

Until next time! 

With Love,
Dan Lawson

Daniel Lawson
Author: Daniel Lawson

Right off the bat I can tell you that I’m not your average data analyst. I’ve spent most of my career running my own business as a photographer and videographer, with a sprinkling of Web Development and SEO work as well. My approach to life and work is very T-shaped, in that I have a small set of specific skills complemented by a very broad range of interests; I like to think of myself as a dedicated non-specialist. Data Analytics, and Programming, started as a hobby that quickly grew into a passion. The more I learned the more I looked for opportunities to pull, manipulate, and join data from disparate sources in my life. I learned to interact with REST APIs for services I used, personal data from services I use like Spotify, and health data captured by my devices. I learned SQL to create and query databases, as well as analyse SQLite files containing my iMessages and Photos data on my Mac. Every technique I learned opened up more possibilities; now I’m hooked and there’s no turning back. Learn More About Me: https://danlsn.com.au