How to Analyze a Good Blockchain? Hindi BF Guide
2025-10-01
Blockchain may sound complicated, but it is easier if we think of it as a digital notebook. This notebook keeps a record of everything safely. People use blockchains for money, games, digital art (NFTs), and even to store important documents.
But here’s the catch: not every blockchain is the same. Some are strong, secure, and very reliable. Others may be weak, slow, or even risky. So, how do we know which blockchain is good?
This is where the Hindi BF Guide comes in. BF here means Blockchain Fundamentals (but you can also remember it as Best Friend), because this guide explains blockchain in a way that feels like a friend is teaching you. Let’s go step by step.
How to Analyze a Good Blockchain
Step 1: Define Your Goal
Before touching data, always ask yourself: What do I want to know?
Examples:
Do you want to see how people used their free tokens after an airdrop?
Do you want to count how many transactions a DeFi (decentralised finance) app had in the last month?
Do you want to follow stolen funds after a hack?
By setting a clear goal, you will not feel lost in a sea of confusing blockchain data.
Read Also: Hindi BF: Finding the Best Fundamental Crypto Projects
Step 2: Set Boundaries
Blockchain data is enormous, almost like a never-ending storybook. You must set limits.
Pick one blockchain to focus on, like Ethereum or Solana.
Choose a time frame, such as the last 30 days.
Decide what type of event to study, such as token transfers or smart contract activity.
This keeps your research clear and focused.
Step 3: Choose How to Get the Data
There are three main ways to access blockchain data:
APIs – Websites like Etherscan or Alchemy give easy access to data.
Run your own node – This gives you full control but needs strong computers.
Use a data lakehouse – A large system that stores data using tools like Apache Iceberg.
Beginners should start with APIs, and later, move to advanced methods.
Step 4: Clean and Organise Data
Raw blockchain data looks messy. It has long codes, confusing logs, and numbers that are hard to read. To make it clear:
Decode logs so they make sense.
Normalise timestamps (so all times look the same).
Add labels to wallets (for example, mark which wallet belongs to an exchange or looks suspicious).
After cleaning, the data becomes clear and easy to study.
Read Also: Layer 2 Blockchain Fundamentals: A Guide for Hindi Mein
Step 5: Build a Scalable System
If you want to handle big data, you need strong tools. A good system may include:
Pipelines like Kafka or Spark (to move data fast).
Storage like Iceberg on S3 (to keep data safe).
Query engines like StarRocks (to ask questions quickly).
ETL tools like PySpark (to prepare data).
This helps when studying millions of blockchain transactions.
Step 6: Ask Smart Questions
Now that your data is ready, you can ask deeper questions:
How did users behave after a big token drop?
Which wallet sent money to the hacker?
Are there strange patterns that may look like fraud?
Using tools like SQL queries, you can find the answers.
Step 7: Optimise for Speed
As data grows, your queries may become slow. To fix this:
Break data into smaller groups (partitioning).
Pre-calculate common results (pre-aggregation).
Use caching for quick access.
Build materialised views for repeated queries.
This makes your analysis smooth and fast.
Step 8: Create Dashboards
Numbers can be confusing if you only see them in raw form. Dashboards turn numbers into charts, graphs, and tables.
A good dashboard should:
Show trends over time.
Use simple, human-readable labels.
Allow you to drill down into details.
Dashboards make blockchain insights easier to share with non-technical people.
Step 9: Real-Time Alerts
Sometimes, you need live updates. For example:
Spotting fraud quickly.
Tracking money laundering.
Following compliance rules.
Real-time alerts will notify you the moment something suspicious happens.
Step 10: Treat Data Like Software
Blockchain analysis is not a one-time job. It is a process that must keep improving.
Use version control (like Git) to track changes.
Monitor system performance.
Upgrade tools when necessary.
Think of it as keeping your tools sharp.
Read Also: Hindi Mein BF: How to Find Crypto Projects with the Best
Why This Matters
Analysing blockchain is important because:
It brings transparency to transactions.
It helps detect fraud and hacks.
It guides business decisions.
It builds trust in the Web3 world.
By following this Hindi BF guide, you can turn messy blockchain data into powerful knowledge.
Read Also: Best Blockchain Development Trends in 2025
Conclusion
Analysing blockchain does not need to be scary. Start small with clear goals and simple tools like APIs. As you grow, you can move into advanced systems with scalable pipelines and dashboards.
Think of it as a journey: from asking simple questions to building powerful systems that uncover deep insights.
In this Bitrue blog article, Hindi BF can also be called Blockchain Fundamentals. This guide is like having a best friend walk you through the process, step by step, clear and simple.
FAQ
What is blockchain analysis?
Blockchain analysis means studying blockchain data to understand transactions, user behaviour, or risks.
Do I need coding skills to analyse blockchain?
Not at the beginner level. You can use explorers like Etherscan. But for deeper analysis, some coding (like SQL or Python) is very useful.
Can blockchain analysis stop scams?
It cannot stop scams completely, but it helps detect them early. Real-time alerts can warn you of suspicious activity.
What is the easiest tool for beginners?
APIs such as Etherscan or Alchemy are the simplest starting point.
Why is cleaning data important?
Because raw blockchain data is messy. Cleaning makes it clear, readable, and ready for insights.
Disclaimer: The content of this article does not constitute financial or investment advice.
