Welcome to
IT Fundamentals
A structured, plain-language training module that takes you from zero to confident in understanding the IT world � its structure, roles, and how to navigate it.
??? Your IT Orientation Starts Here
This module is built for freshers joining any IT-adjacent role � whether you're in HR, business, operations, or tech. By the end, you'll know how software gets built, who builds it, and how to evaluate IT professionals even without a technical background.
A clear mental map of the IT landscape � from how software is built, to what different tech roles actually do day-to-day, to how you can screen or evaluate an IT professional without needing to be one yourself.
- Navigate using the left sidebar � each section is self-contained
- Every topic starts with the outcome, then builds up step-by-step
- Real-world examples (like Zomato, Amazon, a bank) are used throughout to ground concepts
- The final section gives you a ready-to-use screening framework � no tech expertise required
- Revisit the Roles section as a reference anytime you're evaluating or onboarding someone new
A city has roads (networks/infrastructure), buildings (servers/cloud), workers with different jobs (developers, analysts, architects), laws and regulations (security/compliance), construction companies (software vendors like SAP, Microsoft), and a city planning department (SDLC/project management). IT is no different � it's an ecosystem of systems, tools, and people all working in coordination. This module maps that city for you.
SDLC � How Software
Gets Built
The Software Development Life Cycle is the blueprint that every software project follows � from idea to live product.
A working software product or application � built predictably, tested properly, and delivered on time. SDLC is the process framework that makes this happen consistently, not by accident.
"SDLC is to software what a recipe is to cooking. You can improvise, but without a recipe, you risk serving a disaster."
Planning
Define what is being built, why, for whom, by when, and at what cost. This includes feasibility analysis and resource estimation.
Requirements Gathering
Detailed documentation of what the software must do (functional requirements) and how it must perform (non-functional requirements like speed, security).
System Design
Architects and senior engineers decide HOW the system will be built � database structure, APIs, third-party services, tech stack, and system architecture.
Development (Coding)
Engineers write the actual code. Frontend developers build what users see. Backend developers build the logic and data handling behind the scenes.
Testing & QA
Quality Assurance (QA) engineers test the software for bugs, performance issues, security holes, and whether it meets the original requirements.
Deployment
The tested software is moved to a live environment where real users can access it. This involves DevOps engineers, release pipelines, and monitoring systems.
Maintenance & Support
Post-launch: bug fixes, performance improvements, user feedback incorporation, and security patches. Software is never truly "done."
Each phase is completed fully before the next begins. Like building a house � you finish the foundation before the walls. Used in construction software, government projects, banking cores.
Work in short 2-week "sprints." Build a little, test a little, release a little. Get feedback fast. Used by most modern product companies � Flipkart, Swiggy, Razorpay, etc.
Programming Languages �
The Tools of Building
Programming languages are the languages developers use to give instructions to computers. Different languages are suited for different tasks.
You don't need to learn to code � you need to understand why certain languages appear in job descriptions, and what they signal about the kind of work someone does.
Web / Frontend: HTML, CSS, JavaScript, TypeScript
These build everything you see in a browser � the layout, buttons, animations, forms. JavaScript is the engine of the modern web.
Backend / Server: Python, Java, Node.js, Go
These power the logic behind the scenes � processing orders, calculating payments, managing user data, calling databases.
Mobile: Swift, Kotlin, Flutter, React Native
Swift is for iOS (iPhones). Kotlin is for Android. Flutter and React Native let one codebase run on both platforms.
Data & AI: Python, R, SQL
Python dominates data science, machine learning, and AI. R is used in statistics-heavy fields. SQL is universal for querying databases.
Infrastructure / DevOps: Bash, Python, Go, YAML
Used to automate server setup, deployments, and infrastructure management. Not "traditional" programming � more about configuration and automation.
Databases � Where
Data Lives
Every application stores data somewhere. Databases are the organised systems that store, retrieve, and manage that data reliably.
Understanding which type of database is used in a project tells you a lot about the kind of data problem being solved � structured business data, flexible product data, speed-critical caching, or massive analytics.
Relational Databases (SQL) � The Classic
Data is stored in tables with rows and columns � like Excel, but far more powerful. Tables are linked via relationships. Best for structured, business-critical data.
NoSQL Databases � The Flexible Alternative
Data is stored as documents (JSON-like), key-value pairs, or graphs. Better for unstructured, rapidly changing, or massive-scale data.
In-Memory Databases � For Speed
Data is stored in RAM (not disk), making reads/writes near-instantaneous. Used for caching, session management, and real-time features.
Data Warehouses � For Analytics
Built for querying huge historical datasets. Not for live apps � for business intelligence, dashboards, and reporting. Queries can run over billions of rows.
SAP & Enterprise
Software Ecosystems
Large companies don't build everything from scratch. They use massive, pre-built platforms that cover entire business operations � SAP being the most dominant globally.
Understanding SAP tells you why large enterprises (Tata, Reliance, ITC, Infosys clients) have entire teams dedicated to one vendor's software � and what those teams actually do.
SAP (Systems, Applications & Products) is a German software company that makes enterprise resource planning (ERP) software. Think of it as the operating system for a large company's operations � HR, finance, supply chain, procurement, manufacturing, and sales all running on one integrated platform. In India, most large corporates, PSUs, and IT services firms (TCS, Wipro, Infosys) run significant SAP practices.
Financial Accounting & Controlling. Handles all money flows � accounts payable/receivable, balance sheets, cost centres. Used by every large company's finance team.
Human Capital Management. Payroll, attendance, org structure, performance. What many large Indian firms use for their HR backend.
Materials Management. Procurement, inventory, vendor management, purchase orders. Critical for manufacturing and retail firms.
Sales & Distribution. Order management, pricing, billing, delivery. Every sales transaction flows through this module.
Production Planning. Manages manufacturing processes � what to make, when, with what materials. Used heavily by auto and FMCG companies.
The technical backbone � system administration, performance tuning, transport management. Like the IT admin of an SAP landscape.
The programming language used to customise SAP. ABAP developers write code to extend and modify SAP behaviour for specific business needs.
The modern, cloud-ready version of SAP ERP built on an in-memory database. Migration from older SAP ECC to S/4HANA is a massive ongoing industry trend.
Cloud-based HR platform (acquired by SAP). Modern companies are migrating HR from SAP HCM to SuccessFactors for cloud-native HR capabilities.
The world's leading CRM (Customer Relationship Management) platform. Manages sales pipelines, customer data, service tickets. Has its own developer ecosystem (Apex language, Lightning).
Microsoft's ERP + CRM suite. Competes with SAP in mid-market. Tightly integrated with Office 365 and Azure cloud. Popular in companies already deep in the Microsoft ecosystem.
Oracle's flagship ERP product. Major competitor to SAP in finance-heavy industries like banking, telecoms, and utilities. Oracle Fusion is their cloud ERP product.
IT Service Management (ITSM) platform. Manages IT tickets, incidents, changes, and workflows. Every IT team in a large company uses something like ServiceNow.
Cloud Services �
IT's New Infrastructure
Cloud computing means renting computing power, storage, and services over the internet instead of owning physical servers. It's the backbone of modern IT.
Understanding cloud means understanding where modern applications live, how companies scale globally overnight, and why "cloud migration" is one of the biggest initiatives in every large enterprise today.
Infrastructure as a Service
Rent raw hardware � servers, storage, networking. You still manage the OS and everything above it.
Platform as a Service
Rent a managed platform to deploy your code. The provider handles OS, scaling, and patching for you.
Software as a Service
Use ready-made software over the internet. No installation, no maintenance.
?? AWS
Amazon Web Services. The largest cloud provider. 200+ services. Used by Dunzo, Freshworks, Razorpay. Market leader globally.
?? Microsoft Azure
Microsoft's cloud. Dominant in enterprises using Microsoft products. Tata Consultancy Services, Infosys, and most Indian banks use Azure heavily.
?? Google Cloud (GCP)
Google's cloud. Strongest in AI/ML and data analytics. Used by Myntra, Ola, and data-heavy workloads needing BigQuery or AI services.
Containers & Docker
Package an application and all its dependencies into a portable "container" that runs identically anywhere. Docker is the tool; Kubernetes (K8s) is the system that manages thousands of containers at scale.
Serverless / Functions
Write a function (a small piece of code) and let the cloud run it � no server to manage. You pay only for the milliseconds it runs.
IT Roles � Who Does
What in a Tech Team?
IT is not a monolith. Every team has specialists. Here's a map of the most common IT roles, what they actually do, and what skills they carry.
You'll be able to read a job title and immediately understand what problem that person solves, what tools they use, and how they fit into a tech organisation.
????? Frontend Developer
?? Backend Developer
?? Full Stack Developer
?? Data Analyst
?? Data Scientist / ML Engineer
??? DevOps / SRE Engineer
?? Cybersecurity / InfoSec
?? Product Manager (Tech)
?? Solutions Architect
?? QA / Test Engineer
"A developer builds the car. A DevOps engineer maintains the road and traffic system. A data scientist reads the GPS data to find a better route. A product manager decides which city to drive to. QA checks that all the seatbelts work."
Screening IT Talent �
Without Being an Expert
You don't need to code to screen a developer. You need the right framework to ask the right questions and spot the right signals.
A structured approach to evaluate any IT candidate � whether you're in HR, business, or a non-technical hiring manager � by focusing on clarity, real examples, and logical thinking rather than technical jargon.
"Walk me through a project you're proud of � what was the problem, what did you build, and what was the impact?"
What you're listening for: Can they explain clearly without jargon? Do they own their contribution specifically? Do they talk about outcomes (not just tasks)?
"Tell me about a time something broke in production. What happened, and how did you handle it?"
What you're listening for: Calmness under pressure, systematic thinking, honest ownership. Experienced professionals have war stories. No story = limited experience.
"How do you decide how to build something when there are multiple ways to do it?"
What you're listening for: Trade-off thinking. Good engineers weigh speed vs. reliability vs. cost vs. maintainability. They don't just pick what they know best.
"What have you learned in the last 6 months � a new tool, concept, or skill?"
What you're listening for: Self-directed learning is the single most important trait in IT. Technology changes every year. Professionals who stop learning become stale fast.
| Role | Their Core Job (1 sentence) | Key Signal in CV | 1 Smart Screening Question |
|---|---|---|---|
| Frontend Dev | Build what users see and click | Portfolio link or GitHub with visible projects | "Show me something you've built. Walk me through one UI decision you made." |
| Backend Dev | Build the server logic and APIs behind the product | Mentions of APIs, databases, scale (users/req per sec) | "How would you design a system where 1 million users can check their balance at the same time?" |
| Data Analyst | Answer business questions using data | Dashboard/report examples, SQL mentioned, business metrics | "Give me an example of an insight from your data that changed a business decision." |
| DevOps Engineer | Keep systems running smoothly and deployments fast | Docker, Kubernetes, CI/CD tools, uptime/availability metrics | "How do you deploy a new feature without causing downtime?" |
| QA Engineer | Find bugs before users do | Test automation tools, bug count/severity examples | "How do you decide what to automate vs. test manually?" |
| SAP Consultant | Configure and customise SAP for client's business processes | Specific SAP modules (FI, MM, SD), implementation projects, certifications | "Walk me through an end-to-end process you configured in SAP. What business problem did it solve?" |
| Cloud/Infra Engineer | Design and manage cloud infrastructure | AWS/Azure/GCP certifications, cost optimisation results | "Tell me about a time you reduced cloud costs or improved reliability. What did you change?" |
| Product Manager | Decide what gets built, why, and in what order | Metrics-driven impact, cross-functional work, roadmaps | "How do you decide what to build next when everyone on the team wants something different?" |
- Can only describe what their team did, not what THEY specifically contributed
- Uses buzzwords without being able to explain them simply ("We used AI" � ask "what kind? how?")
- No examples of failure, bugs, or mistakes � signals low experience or low honesty
- Cannot explain their work to a non-technical person in 2 minutes
- Lists 20+ technologies on a CV but can't go deep on any single one
- No evidence of learning in the last 12 months
- Defensive or vague when asked "what would you have done differently?"
You don't need to know if someone's code is good. You need to know if they can think clearly, own outcomes, communicate well, and keep learning. These are universal signals that cross all technical roles � and you can evaluate all four without writing a single line of code.