Google Data Analytics Foundation Learning

They call it the black gold of the 21st century, the lifeblood of business decisions, and the ultimate key to unlocking insights: data. And I'm Shibangi Das, an aspiring data analyst with the thirst to conquer its secrets.
1. Building The Mindset To Become a Data Analyst:

To become a Data Analyst the the very first thing you have to do is build the mindset. Let's discuss what the mindset is and why is it important.
Mindset is your inner voice. A set of whispers and choices and how you see yourself and the world.

Again mindset is two types :

Fixed mindset: Here mistakes are seen as proof of not being good enough.

Growth mindset: Mindset embraces effort and sees possibilities for advancement.
Mindset is important because it acts as the internal fuel and compass for your life. It directly impacts how you approach and experience the world, influencing your Resilience, Learning and Achievement, Motivation and Well-being, Relationships and Interactions, and Overall Life Experience.
I practiced lots of learning log activities to examine how I fit this role and through these learning logs, my curiosity to learn more about Data analysis has increased.2

1. What is Data and How Data is useful for a Business Decision?

Data, in its simplest form, is information. It can be any kind of information, from numbers and statistics to text, images, and even sounds. In the context of business, data refers to all the information we collect about our customers, operations, market, and competitors.

Data is a powerful tool that can be used to gain insights, make informed decisions, and drive business success. By effectively collecting, analyzing, and utilizing data, businesses can gain a significant competitive advantage in today's data-driven world.

1. Data Analysis Process And Data Life Cycle:

   These are two important terms that I have learned.
   While distinct, these concepts are deeply intertwined. The data life cycle provides the foundation for effective data analysis. High-quality, well-managed data leads to more accurate and reliable insights. Conversely, the analysis process informs data management decisions, identifying potentially valuable data for retention or prompting data cleansing efforts.

   Both the data analysis process and data life cycle are iterative and adaptable. Depending on the complexity of the data and the problem at hand, you may revisit certain stages or adjust your approach as you gain new insights.

2. How to Solve A Problem through Business Case Studies?

   To conquer business case studies, start by dissecting the problem, and peeling back its layers to understand its core. Then, embark on a quest for knowledge, seeking out relevant cases like seasoned treasure hunters. Analyze each like a skilled alchemist, extracting their essence and filtering out the irrelevant. Apply these newfound insights to your challenge, adapting them like a tailor crafting a bespoke solution. Finally, measure and iterate, learning from each step and refining your approach until you conquer your business, Everest.

Thank you...