What Is Data Analytics?

What the job actually is, the three types of analytics, and why this career matters for YOUR life.

~18 minutes

📌 Before You Start

What you need: Nothing. No tools needed for this module. Just you and your brain.

What you’ll do: You’ll understand what data analytics actually IS — and more importantly, why it matters for YOUR career. By the end, you’ll have created your first real dataset in Google Sheets.

What you’ll need open for Practice: Google Sheets at sheets.google.com (free, sign in with any Google account).

💡 The Concept

Data analytics is finding patterns in information to help make better decisions. That’s it.

Every company collects data — sales numbers, customer behavior, website clicks, employee hours, inventory counts, patient outcomes. But data sitting in a spreadsheet doesn’t help anyone. It’s just numbers.

A data analyst turns that raw data into answers:

“Why did sales drop in March?”
“Which product do customers return most?”
“Where are we losing money?”
“Which patients are at highest risk?”
“Which marketing channel drives the most revenue?”

You are the person who answers those questions. You are the bridge between raw data and good decisions.

Three types of analytics — know these, because interviewers ask:

Descriptive

What happened?

Summarizing historical data. Sales reports, dashboards, averages. Most common type.

Diagnostic

Why did it happen?

Drilling down to find the root cause. Why did sales drop? Which region? Which product?

Predictive

What will happen next?

Using patterns from the past to forecast the future. Comes with experience and data science skills.

As a beginner, you will focus on descriptive and diagnostic. Predictive comes with time and more advanced skills. You will be useful and employable with descriptive + diagnostic alone.

🔗 Why It Matters

Data analyst roles are among the fastest-growing jobs globally.

Every industry needs them:

Healthcare — patient outcomes, cost analysis, resource planning
Finance — risk, fraud detection, investment performance
Education — student success, enrollment trends, budget allocation
Government — policy analysis, public health, infrastructure
Retail — inventory, customer behavior, pricing
Tech — product metrics, user behavior, A/B testing

Median salary: $70,000–$95,000 USD. Entry-level roles often start at $55,000–$70,000 even without a degree, if you have the skills.

The SAP advantage: SAP skills (Phase 5 of this course) specifically open doors at enterprise companies — Fortune 500 companies, large corporations, government agencies. SAP FI/CO professionals earn $85,000–$140,000+. You are building exactly that combination.

You are building a real, in-demand, portable skill set. These skills transfer between industries. You are never locked in.

🖐️ Practice

You are going to do your first act of data analytics right now. Yes, really. Open Google Sheets.

Go to sheets.google.com and sign in with any Google account. Click the + Blank button to create a new spreadsheet.

Click on the title at the top (it says “Untitled spreadsheet”). Change it to: My First Data Set

In row 1, type these five column headers, one per cell: Day | Mood (1-5) | Hours Slept | Water Glasses | Energy (1-5)

Fill in the last 5 days from memory. Estimates are completely fine — exact precision is not the point. Enter Monday through Friday (or whatever your last 5 days were). For Mood and Energy use a scale of 1 (terrible) to 5 (great).

Look at your data. Ask yourself: Is there a pattern? When your sleep was higher, was your energy higher? Was your mood better on days you drank more water? You don’t need statistics for this — just look.

Pause here. You just did data analytics. You collected data, organized it into a structured format, and looked for patterns. That IS the job. In a company, the data is bigger and the stakes are higher — but the process is identical.

🛑 Good stopping point if you need a break. Bookmark this page and come back anytime.

🧠 Brain Break

You just shifted how you see the world. Data is everywhere now — every number, every list, every pattern is potential data. That is a real cognitive shift. Your brain just did something.

Take a breath. Notice 3 things around you. Each one is a potential data point.

Look away from the screen 2 slow breaths Notice 3 things near you Stand up if you can

Take at least 90 seconds. The next section will be here when you get back.

✅ You Got This

The ONE thing to remember from this module:

Data analytics = finding patterns in information to make better decisions. You are going to get very good at this.

What comes next: Module 2 introduces SQL — the language you use to talk to databases. You will write your first real SQL query and run it live in a browser. No installation needed.

← Phase 1 Home 📋 Course Home Module 2: SQL Foundations →