Introduction

“Data is the fuel of the 21st Century”, said a wise person once. Today, we find LLMs being used in almost every aspect of our day-to-day lives, making this statement extremely timely. An average human being in this world is exposed to some sort of technology that derives insights from the activity performed by them over a while or based on the choices they make. Right from the moment you wake up and long until winding down your day, you see data everywhere.

When you realize that data has the power to shape the way you think, act and perform every day, you can either be scared about it, limiting your exposure or you can spend some time learning about how data works and how you can harness its power to make your life more comfortable.

To gain a deeper understanding of data and to explore ways to make tangible conclusions from the data that surrounds us every day, I tried to lay my foundations strong by taking this quite an amazing course on Coursera known as “Foundations: Data, Data, Everywhere”.

What to expect from the course?

This course is a part of the Google Data Analytics Professional Certificate, out of which this is the first module.

It aims to explain to the learners:

  • About the careers that data can offer.

  • The use of organizing, processing, and analyzing data and much more.

The main goal of this course is to build fundamentals about why is it important to learn about data, the pros of trying to understand the data and the cons of leaving the data unstructured and disorganized.

Furthermore, the instructors discuss the use of data analytics and how analyzing the data can impact the business in real time.

My Experience

  • In Week 1, the instructor introduces the learners to data analytics where he talks about the day-to-day use cases of data analytics. Then he also briefly touches on the phases involved in data analytics and the roadmap that lies ahead for someone who is trying to explore the field of data analytics.

    Data Analytics is the collection, transformation and organization of data to conclude, make predictions, and drive informed decision-making.

  • In Week 2 of this module, the instructor relates how he was able to notice a pattern in real life which helped him to make informed data-driven decisions. This is where he introduces the learners to analytical skills, analytical thinking and their aspects.

    Analytical skills are qualities and characteristics associated with solving problems using facts.

    • The instructor then dives deep into the five aspects of analytical skills, which are: curiosity, understanding context, having a technical mindset, data design, and data strategy. The way the instructor relates these five aspects to real-life scenarios makes it easier for the learner to understand and relate.

    • After having an understanding of analytical skills, the instructor then explains analytical thinking and its aspects deeply. Here he also talks about gap analysis and data-driven decision-making in detail.

    An easier way to think about analysis is turning data into insights.

    • Throughout the module, learners are made to write a learning log, a place where they relate their understanding of the concepts to real-life scenarios. This will help the learners to identify the patterns within the data and come to conclusions to improve their understanding of the task at hand.

  • After understanding Data Analysis in Week 1 and getting a proper understanding of Analytical skills and thinking in Week 2, this is where we dive deep into understanding, visualizing and utilizing data. In Week 3, the learners are introduced to the life cycle of data. The goal of this Week is to understand how “Data Analysts bring data to life?”.

    • The instructor talks in detail stages of the data life cycle which are: Plan, Capture, Manage, Analyze, Archive, and Destroy. The Self-Reflection assignments that are placed within every week’s learning material help the learner to keep track of their journey.

    • This course also explores the tools that are used by Data Analysts to determine the patterns within the data. This makes the learners realize the importance of choosing the right tool for the right job. This course also briefly looks into the tools such as Spreadsheets, Query languages, and Visualisation Tools.

  • In Week 4, we talk business, that is, we talk about the “ins and outs of core data tools”. This Week introduces the Key Data Analyst tools which are Spreadsheets(Excel or Google), SQL, and Data Visualisation. There were Knowledge Tests after every course helping the learners to retain whatever they have learned.

  • In the final week, Week 5, the instructor goes on to tell the viewers about the job of a data analyst, the power of data in business and how data analysts are useful throughout the ecosystem.

    • In the end, the learners are introduced to many real-life people who deal with huge data sets and provide solutions to business problems in the field and how they rely on unbiased data to make a decision.

Conclusion

Data analytics is something that is becoming popular day by day especially when we are relying so much on data to lead our lives properly. Data analytics is indeed a burgeoning field, integral to our data-driven lives. In the journey to master this craft, this course stands as an invaluable stepping stone. In my opinion, this course is the best way for someone new to the field to begin their career. This course was taught by fantastic instructors who explained concepts with incredible precision. The course was a great experience for me, and I recommend it to anyone new to this field.