Recipe to become a Data Analyst

Episode 1

This blog is my understanding of the Foundations of Data Analytics course by Google aiming to help every beginner and data enthusiast.

Well, it’s true that data is the new oil and our future holds the truth that data is always growing. We haven’t seen a single piece of evidence that data is shrinking.

So what is data, data science, analytics and analysis? Do all these words puzzle you? Don’t worry here is the catch.

Data is the collection of facts and Data science, the discipline of making data useful. Data Science is not a single subject or a job role, instead, it’s an umbrella term for multiple disciplines.

Whereas Data Analytics is the Science of Data and Data analysis is the collection, transformation & organization of the data to conclude, make predictions and drive informed decision–making.

Data Science Umbrella

The above Venn diagram should give you a clear understanding, this is where all the data enthusiast family finds themselves.

If you are a beginner and want to understand where do you want to land up go with your strengths and personality, here is an analogy for you.

Let’s say you’re a person who is, very careful about protecting decision-makers from coming to the wrong conclusion than you’re passionate about Statistics. If performance and automation are something that excites you, then Machine Learning is your area. And last but not least if you encounter speed in your veins and want to explore vast amounts of data and are super creative to discover potential insights and then you are into analytics.

And this blog is dedicated to all the data analysts.

A Data Analyst is someone who collects, transforms & organizes data to make informed decisions. And how is this different from a data scientist? Here’s a good way to think about it. Data scientists create new questions using data, while analysts find answers to existing questions by creating insights from data sources.

Why are they so powerful?

• They have a data mindset
• They are versatile thinkers
• They have a very effective way to influence an organization.

Developing a data mindset needs analytical thinking and skills which involves qualities and characteristics to understand the problem and solve it using the data. This will enable you to tap into the power of data to do all kinds of amazing things.

Key to developing data mindset

Every powerful person has a technique & a secret to their success, today in this blog I’m sharing with you the main principle followed in data analysis if practised religiously will make you a Data God.

Introducing you to the secret recipe of 6 phases of Data Analysis — the process of going from data to decision

1. Ask Business Challenge/Objective/Question
2. Prepare Data generation, collection, storage, and data management
3. Process Data cleaning/data integrity
4. Analyze Data exploration, visualization, and analysis
5. Share Communicating and interpreting results
6. Act Putting your insights to work to solve the problem

It is easy to get mired in data analytics wormholes and overlook the common goal. The most important thing to remember while starting on a data analytics project is to understand the business problem thoroughly. It’s key in bringing data-driven insights & decisions.

While the data analysis process will drive your projects and help you reach your business goals, you must understand the life cycle of your data to use that process. To analyze your data well, you need to have a thorough understanding of it.

The life cycle of data is to plan, capture, manage, analyze, archive and destroy.

1. Plan: Decide what kind of data is needed, how it will be managed, and who will be responsible for it.
2. Capture: Collect or bring in data from a variety of different sources.
3. Manage: Care for and maintain the data. This includes determining how and where it is stored and the tools used to do so.
4. Analyze: Use the data to solve problems, make decisions, and support business goals.
5. Archive: Keep relevant data stored for long-term and future reference.
6. Destroy: Remove data from storage and delete any shared copies of the data.

Everything is so overwhelming, right? Well, it’s just a beginning, gear yourself up.

Businesses need a way to control all that data so they can use it to improve processes, identify opportunities and trends, launch new products, serve customers, and make thoughtful decisions. Take a look at this article from HBS on how some companies are harnessing the power of data.

I like to think that data analytical projects are like a mystery-solving case.

Data + business knowledge = mystery solved

All we need is a perfect blend of data with business knowledge, plus maybe a touch of gut instinct.

Data Analysts make use of their toolkits to fuel their knowledge like spreadsheets, Databases, Querying & programming knowledge and visualization tools.

Now I’ll take leave and let you get ready with your toolkit to kickstart into the detailed analysis process and be Data Literate in the upcoming series.

Check out the inspirational talk from “Godfather of Data Literacy”

Be Curious & Creative

Coming up we will learn to answer below questions …

· What are some considerations or preferences you want to keep in mind when making a decision?

· What kind of information or data do you have access to that will influence your decision?

· Are there any other things you might want to track associated with this decision?