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Sachin Kumar

@Sachintukumar

Aug 18

Think of data modeling as brain of Power BI — without it, everything else is just decoration

When I first started using #PowerBI, I thought visuals & DAX were “main game.”
But soon I realized: If your data model is weak, nothing else will save your dashboard.

A Complete🧵

Think of it like this:
1) Visuals = House front
2) DAX = Electricity & plumbing
3) Data Model = Foundation
Without a strong foundation, everything else collapses.

☑️ What exactly is a Data Model?
It’s simply the way you organize & connect your data so Power BI can:
- Understand it
- Perform fast calculations
- Show correct insights
And this magic happens inside Model View of Power BI.

Here are the building blocks of a strong data model

1) Fact Table → Numbers & metrics (e.g., Sales, Revenue)
2) Dimension Table → Descriptions/details (e.g., Products, Dates, Customers)
3) Relationships → Connections between tables (usually 1 → many)
4) Primary Key → Unique ID (e.g., ProductID)
5) Foreign Key → The matching ID in another table (e.g., Sales[ProductID])

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Sachin Kumar

@Sachintukumar

Aug 15

Top #SQL Q&A Every Data & Business Analyst Must Master

Complete 🧵

Q) @Oracle SQL Question:

We have two tables:
1️⃣ employee_contract
base
commission
quota
accelerator
2️⃣ deals → All deals they made, with deal amounts.

We need to calculate:
If total deals < quota →
total_compensation = base salary + commission * total deals
If total deals ≥ quota →
total_compensation =
base salary
commission * quota (normal commission for sales up to quota)
commission * accelerator * (total deals - quota) (boosted commission on sales after quota)

Q2) @salesforce

Write a query to calculate average annual revenue per Salesforce customer in three market segments: SMB, Mid-Market, & Enterprise. Each customer is represented by a single contract. Format output to match the structure

Read 7 tweets

Sachin Kumar

@Sachintukumar

Jul 20

Not every deal-maker hits the target — SQL finds who actually did.

Oracle #SQL Interview Question

A Complete thread

Q) As a data analyst on @Oracle Sales Operations team, you are given a list of salespeople’s deals, & annual quota they need to hit.

Write a query that outputs each employee id & whether they hit quota or not ('yes' or 'no'). Order the results by employee id in ascending order

Definitions: - deal_size: Deals acquired by a salesperson in the year.

Each salesperson may have more than 1 deal. - quota: Total annual quota for each salesperson.

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Sachin Kumar

@Sachintukumar

May 6

Do You Really Know How #SQL Executes Your Query?

Let’s talk about actual execution order of an SQL query — it’s not order you write it in!

🧵

Even though we write SQL like this:

SELECT
FROM
WHERE
GROUP BY
HAVING
ORDER BY
LIMIT

Internally, SQL follows a different execution flow

🎯 INTERVIEW TIP:
Why can’t you use SELECT aliases in WHERE clause?
Because WHERE runs before SELECT!

Mastering this flow is crucial for writing optimized queries & cracking SQL interviews.

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Sachin Kumar

@Sachintukumar

Mar 27, 2024

📝Day 35 of #Deeplearning

✅Topic - Backpropagation in CNN

▫️ #BackPropagation is an algorithm to train neural networks. It is the method of fine-tuning weights of a neural network based on error rate obtained in previous epoch (i.e., iteration)

A Complete 🧵

✅Backpropagation is an algorithm for supervised learning of artificial neural networks using #gradientdescent

Given an artificial neural network and an error function, method calculates gradient of error function with respect to neural network's weights using chain rule

▫️ Total Trainable Parameters-

▫️ Forward Propagation-

Read 13 tweets

Sachin Kumar

@Sachintukumar

Mar 24, 2024

✅Day 32 of #Deeplearning

📝Topic - Padding & Strides

▫️ #Padding is simply a process of adding layers of zeros to our input images

▫️ #Stride describes step size of kernel when you slide a filter over an input image

A Complete 🧵

▫️ Padding is simply a process of adding layers of zeros to our input images.

The purpose of padding is to preserve original size of an image when applying a #convolutional filter & enable filter to perform full convolutions on edge pixel

▫️ So to prevent this-

We will be using padding of size 2 (i.e. original image(5) – feature map(3)).

It is also known as zero padding because we are padding it with 0

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