TotalEnergies — September 2026

Scenario based  Interview Questions & Answers for Data Analyst

1. Scenario: You are working on a SQL database that stores customer information. The database has a table called "Orders" that contains order details. Your task is to write a SQL query to retrieve the total number of orders placed by each customer.   Question:   - Write a SQL query to find the total number of orders placed by each customer. Expected Answer:     SELECT CustomerID, COUNT(*) AS TotalOrders     FROM Orders     GROUP BY CustomerID;

2. Scenario: You are working on a SQL database that stores employee information. The database has a table called "Employees" that contains employee details. Your task is to write a SQL query to retrieve the names of all employees who have been with the company for more than 5 years.   Question:   - Write a SQL query to find the names of employees who have been with the company for more than 5 years. Expected Answer:     SELECT Name     FROM Employees     WHERE DATEDIFF(year, HireDate, GETDATE()) > 5;

Power BI Scenario-Based Questions

1. Scenario: You have been given a dataset in Power BI that contains sales data for a company. Your task is to create a report that shows the total sales by product category and region.     Expected Answer:     - Load the dataset into Power BI.     - Create relationships if necessary.     - Use the "Fields" pane to select the necessary fields (Product Category, Region, Sales).     - Drag these fields into the "Values" area of a new visualization (e.g., a table or bar chart).     - Use the "Filters" pane to filter data as needed.     - Format the visualization to enhance clarity and readability.

2. Scenario: You have been asked to create a Power BI dashboard that displays real-time stock prices for a set of companies. The stock prices are available through an API.   Expected Answer:     - Use Power BI Desktop to connect to the API.     - Go to "Get Data" > "Web" and enter the API URL.     - Configure the data refresh settings to ensure real-time updates (e.g., setting up a scheduled refresh or using DirectQuery if supported).     - Create visualizations using the imported data.     - Publish the report to the Power BI service and set up a data gateway if needed for continuous refresh.

3. Scenario: You have been given a Power BI report that contains multiple visualizations. The report is taking a long time to load and is impacting the performance of the application.     Expected Answer:     - Analyze the current performance using Performance Analyzer.     - Optimize data model by reducing the number of columns and rows, and removing unnecessary calculations.     - Use aggregated tables to pre-compute results.     - Simplify DAX calculations.     - Optimize visualizations by reducing the number of visuals per page and avoiding complex custom visuals.     - Ensure proper indexing on the data source.

Free SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v

Like if you need more similar content

Hope it helps :)

🔄  📥 Nueva ACTUALIZACIÓN 🚨

✔️ Para ver las aplicaciones que compartimos deben instalar la tienda WEB-TOOLS:

Link official web 💳 apkdescargas.com

Link official telegram 💳 t.me/+PEeV1ZzS4K5hYTFh

❤️‍🔥Si ya tienes instalada la tienda WEB TOOLS ingresa a ella, todos los días tenemos aplicaciones disponibles para que disfruten de esas apps totalmente gratis.

🔄  📥 New UPDATE 🚨

✔️ To see the applications we share you must install the WEB-TOOLS store:

Official web link 💳 apkdescargas.com

Official telegram link 💳 t.me/+PEeV1ZzS4K5hYTFh

❤️‍🔥If you already have the WEB TOOLS store installed, enter it, every day we have applications available for you to enjoy those apps totally free.

🔄  📥 Nova ATUALIZAÇÃO 🚨

✔️ Para ver as aplicações que compartilhamos, você deve instalar a loja WEB-TOOLS:

Link oficial da web 💳 apkdescargas.com

Link oficial do telegrama 💳 t.me/+PEeV1ZzS4K5hYTFh

❤️‍🔥Se você já tem a loja WEB TOOLS instalada, insira-a, todos os dias temos aplicativos disponíveis para você aproveitar esses aplicativos totalmente de graça.

CP Trade to Earn: 10,000,000 CP in Total Rewards

Campaign Period: Sep 2 – Sep 14, 14:30 UTC

Earn from 2 reward tracks simultaneously:

Equal-share Rewards — 1,600,000 CP Trade CP/USDT Spot with at least 200 USDT in total volume to share the pool equally. Max 167 CP/user.

Volume Share Rewards — 8,400,000 CP Trade at least 3,000 USDT in total volume to share the pool, boosted by 2 multipliers. Max 50,000 CP/user.

Early-bird Multiplier Days 1–2: ×1.5 | 3–5: ×1.4 | 6–8: ×1.3 | 9–11: ×1.2 | 12–13: ×1.0

Trading-days Multiplier 1–2 days: ×1.0 | 3–5: ×1.1 | 6–9: ×1.2 | 10–13: ×1.3

Trading volume requirements are based on raw volume before multipliers.

Rewards distributed by Sep 16, 14:30 UTC.

Join now

Our Socials:

⚜️ Sign up | OKX Announcement | OKX Campaign | TG | DC | OKX Orbit | Join Affiliate | CN TG | CN DC

‼️Please check the authenticity of all OKX links or channels at OKX channel verification

🔄  📥 Nueva ACTUALIZACIÓN 🚨

✔️ Para ver las aplicaciones que compartimos deben instalar la tienda WEB-TOOLS:

Link official web 💳 apkdescargas.com

Link official telegram 💳 t.me/+PEeV1ZzS4K5hYTFh

❤️‍🔥Si ya tienes instalada la tienda WEB TOOLS ingresa a ella, todos los días tenemos aplicaciones disponibles para que disfruten de esas apps totalmente gratis.

🔄  📥 New UPDATE 🚨

✔️ To see the applications we share you must install the WEB-TOOLS store:

Official web link 💳 apkdescargas.com

Official telegram link 💳 t.me/+PEeV1ZzS4K5hYTFh

❤️‍🔥If you already have the WEB TOOLS store installed, enter it, every day we have applications available for you to enjoy those apps totally free.

🔄  📥 Nova ATUALIZAÇÃO 🚨

✔️ Para ver as aplicações que compartilhamos, você deve instalar a loja WEB-TOOLS:

Link oficial da web 💳 apkdescargas.com

Link oficial do telegrama 💳 t.me/+PEeV1ZzS4K5hYTFh

❤️‍🔥Se você já tem a loja WEB TOOLS instalada, insira-a, todos os dias temos aplicativos disponíveis para você aproveitar esses aplicativos totalmente de graça.

REPUTATION BANK results are here!! Week 49 ( August 26 – September 2)

🌱 Total invested: 2860 reputation 💰 Prize: $157 for 43 winners ⭐ Top moderator: AwIwo

➡ CHECK THE FULL LIST OF WINNERS HERE

The more active you are, the better your chances of winning. Every point counts!

Type BANK in chat and make your deposit today!

❤ 50 reactions + 50 comments = PROMO CODE

😜🥳👽👍 👉 3rS2Y164 - Value: $5 - Requirement: 5000$ wagered in the last 7 days - Total Drop Limit: 50 activation

Links: Website | X (Twitter) | Instagram | CHAT | YouTube | TikTok

Sector 2A ( near swaminarayan temple Sec 2 & infocity)

For Girls- 3rd floor with terrace total two room, One room khali che (No bed,no cupboard, no kitchen) Room total rent 5000 + light bill. (2500/girl + light bill) maximum 2 girls  room ma  rahi ske che.

M- 9265568856(room owner)

For Exam Update :- 👉 https://t.me/yugvandanalibrary

For Rooms :- 👉 https://t.me/GANDHINAGARROOMS

રૂમ આપવાની જાહેરાત માટે 👉 @gandhinagar2025

Puoi leggere libri sulla spiritualità. Puoi guardare video sulla coscienza. Puoi comprendere simboli, meditazione, energia e mente. Ma esiste una differenza enorme tra comprendere qualcosa e viverla. La trasformazione avviene nelle cose apparentemente più semplici: come inizi la giornata, come utilizzi il corpo, dove porti l’attenzione, come reagisci ai pensieri, cosa fai quando perdi disciplina, come utilizzi la tua energia. È qui che la conoscenza diventa pratica. Ed è questa l’idea dietro Rigenerazione Totale: non riempirti di altre informazioni, ma aiutarti a ritrovare presenza, ordine e direzione.

📖 Rigenerazione Totale — Amazon https://www.amazon.it/dp/B0HH9VG818

🎯 POCKETOFFER CHALLENGE 🎯 🔼Reach 5K POFT & Get 2 USDT🔼

Ready for a new challenge? 👀🔥 It’s time to play, earn, and grab your reward!

💡 How to join: 🎮 Play games on PocketOffer 💎 Reach a total of 5,000 POFT earned 💵 Complete the challenge and get 2 USDT

💥REWARD CONDITIONS

✅ A total of 5,000 POFT is calculated based on completing in-game tasks

✅ Subscribe to the PocketOffer channel

✅ Comment your UserID under this post

✅ Each user can participate only once

🚀 Start playing now and hit 5K POFT! Don’t miss out — rewards are waiting 🦊💰

🔔 Subscribe to the PocketOffer channel and stay instantly informed on every new update. 🚀

👛 PocketOffer Gaming hub | Community Notification | Support

«Скажи мне, кто твой шурин, и я скажу, годен ли ты»: зачем Минобороны собирает досье на всю родню?

В соцсетях очередной переполох: заголовки кричат, что военкоматы вот-вот залезут в выписки по картам каждого призывника, пересчитают кредиты его бабушки и проверят дипломатические паспорта троюродного кота.

Как обычно, дьявол кроется в юридических формулировках. Давайте снимем панику и разберем свежий проект приказа Минобороны без иллюзий, но с капелькой здорового скепсиса.

1. Кого на самом деле сканируют «цифровым рентгеном»? Речь идет вовсе не о рядовых срочниках. Документ разработан строго под пункт 6 статьи 53 ФЗ «О воинской обязанности и военной службе». Под тотальный аудит попадают: • претенденты на особые, чувствительные воинские должности; • контрактники, претендующие на спецпозиции; • абитуриенты военных вузов и училищ.

То есть проверять будут тех, кому предстоит работать с секретными технологиями, сложной техникой и государственной тайной.

2. Глубина погружения: от кредитов до тайных пристрастий Список собираемых данных действительно внушает уважение даже Шерлоку Холмсу. Ведомство сможет законно запросить через систему СМЭВ: • Финансы: декларации 3-НДФЛ, банковские счета, статус банкрота и просрочки по займам свыше 300 000 рублей (с долгами на спецслужбу путь закрыт); • Документы и тайны: наличие всех загранпаспортов (включая служебные), статус иноагента, получение денег из-за рубежа и членство в политобъединениях; • Здоровье и прошлое: учеты по наркологии/психиатрии, тяжелые диагнозы, судимости (даже закрытые по примирению сторон) и даже «автомобильные грехи» с ДТП.

3. Семейный подряд под лупой Самый пикантный пункт — пункт 4 приложения: аналогичный досье-пакет военные чиновники вправе поднять на супругов, родителей, детей, родных братьев, сестер, а также… родителей и родственников супруги! Теперь перед свадьбой будущим офицерам явно придется запрашивать у тестя кредитную историю и проверять отсутствие иностранных грантов.

Итог: Никакой «тотальной слежки за всеми подряд» здесь нет — это стандартизация глубокого спецконтроля (Counterintelligence & Vetting) для допуска к стратегическим должностям в едином цифровом окне.

🇷🇺 Цифровой рубль для чайников: зачем Россия запустила третью форму денег и как это изменит наши кошельки

Вокруг этой темы ходит огромное количество мифов и страшилок из разряда «тотальный контроль» и «деньги, которые сгорят через месяц». Давайте разберем этот масштабный финансовый маневр максимально простым языком, без заумных терминов, и поймем, как на этом заработать (или подстраховаться).

❓ Что такое цифровой рубль на пальцах?

Сейчас у нас есть две формы денег: наличные (купюры в кармане) и безналичные (цифры на балансе в приложении Сбера, Т-Банка или Альфы). Цифровой рубль — это третья форма денег. Это уникальный цифровой код (токен), который выпускает напрямую Центральный банк РФ (ЦБ). Главное отличие, которое нужно понять: когда вы держите деньги на карте, вы фактически одолжили их вашему банку. Если банк обанкротится, деньги придется возвращать через систему страхования вкладов (и то с лимитом). Цифровой рубль лежит не в коммерческом банке, а на специальной платформе самого Центробанка. ЦБ обанкротиться не может по определению — это главный кассир страны.

⚙️ Как это будет работать в жизни?

Для обычного человека процесс будет выглядеть привычно и просто: В приложении любого вашего банка (например, Сбера) появится новая кнопка: «Цифровой кошелек».

Вы сможете обменять свои обычные безналичные рубли с карты на цифровые в соотношении 1 к 1. Никаких комиссий за этот обмен нет. Оплачивать покупки можно будет через QR-коды (как через СБП) или специальным касанием телефона, причем даже без доступа к интернету (офлайн-режим — код запишется на чип телефона и передастся на кассу).

🟢Плюсы для обычных людей и бизнеса

✅ Абсолютная бесплатность для граждан: Все переводы цифровых рублей между физическими лицами (например, перевод маме или другу) будут полностью бесплатными. Никаких лимитов в духе «до 100 тысяч в месяц без комиссии, а дальше плати» здесь не будет.

✅ Дешевизна для бизнеса: Магазины сейчас платят банкам огромные комиссии за то, что вы прикладываете карту к терминалу (эквайринг — от 1% до 3% от стоимости товара). Для цифрового рубля ЦБ установил фиксированную копеечную комиссию для бизнеса (всего 0,3%). Это должно снизить издержки продавцов и, в теории, притормозить рост цен.

✅ Безопасность: Каждый цифровой рубль имеет свой уникальный номер. Если у вас украдут такие деньги или вы отправите их мошенникам, ЦБ сможет по цепочке блокчейна отследить движение каждого токена и мгновенно заблокировать его на кошельке вора.

⚠️ Жирные минусы и ограничения (О чем молчит ЦБ)

Инвесторам и трейдерам важно понимать, что цифровой рубль создавался не для заработка. У него есть жесткие экономические тиски:

❌ Никаких процентов на остаток и кэшбэков: На цифровые рубли не начисляются банковские проценты. На них нельзя открыть вклад. За покупки цифровым рублем банки не будут начислять вам мили или рублевый кэшбэк. Банкам это просто невыгодно — эти деньги лежат не у них.

❌ Целевое назначение («окрашивание» денег): Государство может запрограммировать (через смарт-контракты) определенные цифровые рубли. Например, если вам выплатят детские пособия или субсидию на строительство дома цифровыми рублями, их технически невозможно будет потратить на покупку алкоголя, акций на бирже или криптовалюты. Код просто заблокирует операцию на кассе.

❌ Тотальная прозрачность: Для налоговой (ФНС) и финмониторинга ваши траты станут прозрачными на 100%. Скрыть доходы или провести «серую» сделку внутри платформы ЦБ физически невозможно.

🛠 Стратегический план: что делать инвесторам и трейдерам?

Запуск цифрового рубля — это мощный шаг в сторону цифровизации, но для защиты и приумножения капитала нужно выстраивать четкую стратегию:

➡️Не держите там крупные суммы: Используйте цифровой кошелек только как транзитную точку для бесплатных переводов или быстрых оплат без интернета. Держать там капитал бессмысленно — инфляция сожрет его быстрее, так как доходности в 0% годовых.

➡️Переливайте избыточную ликвидность в твердые активы: В условиях, когда контроль за фиатными деньгами со стороны государства становится абсолютным, ценность децентрализованных и дефицитных активов взлетает до небес. Часть свободных денег из традиционной системы должна уходить в физическое золото (инвестиционные монеты) и, конечно, в Биткоин (BTC) и стейблкоины (USDT).

➡️Белый комплаенс для крипты: На фоне зажима «серых» P2P-обменников банками, легальные шлюзы покупки крипты (например, под залог в Сбере или через официальные кастодиальные сервисы) становятся безальтернативными. Цифровой рубль позволит государству моментально вычислять тех, кто гоняет миллионы через карты подставных лиц (дропов). Переводите торговлю криптой на рельсы официального декларирования, чтобы защитить свои карты от вечной блокировки по 115-ФЗ.

✅ Итог: Цифровой рубль — это удобный и безопасный инструмент для повседневных расчетов и госвыплат, но плохой вариант для сохранения богатства. Пользуйтесь технологиями для удобства, но капитал храните в независимых дефляционных активах.

📞Связь с менеджерами: @Olga_FiboManager или @alexkingsmann

▶️ YouTube | 🇷🇺 RuTube

🟠 Лучшая биржа для торговли криптой

📱 Покупка крипты в Telegram-кошельке

Spot Bitcoin ETFs Saw Total Net Outflows of $ 236 Million

According to SoSoValue data, on September 1 ET, U.S. spot Bitcoin ETFs saw total net outflows of $ 236 million. U.S. spot Ethereum ETFs saw total net inflows of $ 10.9528 million, marking 12 consecutive days of net inflows. — link

President Trump:

“I’m not trying to force Iran to the bargaining table, as ABC Fake News reported. I couldn’t care less if they sign a worthless, to them, agreement. I like our position now much better, with almost total control of the Hormuz Strait, and their economy totally collapsing. They are just playing out the inevitable. When are the Iranian people going to rise up and fight?”

This asks:

Which employees earn more than the average salary of their own department?

The inner query depends on the current employee's department. This is more advanced than a basic subquery.

2️⃣4️⃣ Why Correlated Subqueries Matter

Suppose: IT Average salary = ₹80,000, HR Average salary = ₹60,000

An employee earning ₹75,000: Could be below IT average, Could be above HR average

So comparing everyone to the overall company average isn't enough. A correlated subquery allows you to compare each employee to the relevant group.

2️⃣5️⃣ Subquery vs JOIN

Sometimes the same problem can be solved using either a subquery or a JOIN.

For example, finding customers with orders can be done with: WHERE EXISTS (...) or: JOIN Orders ...

Neither is universally better.

The right choice depends on: What result you need, Whether duplicates matter, Query readability, Database optimizer, Data structure

Focus on understanding the logic rather than memorizing one preferred method.

2️⃣6️⃣ A Very Common Interview Problem

Question:

Find employees earning more than their department's average salary.

A correlated subquery solution:

SELECT e.Name, e.Department, e.Salary FROM Employees e WHERE e.Salary > ( SELECT AVG(e2.Salary) FROM Employees e2 WHERE e2.Department = e.Department );

This is an excellent interview question because it tests: Subqueries, Aggregation, Correlation, Business logic

2️⃣7️⃣ Another Interview Problem

Question:

Find customers whose total sales are greater than ₹1,00,000.

Using a derived table:

SELECT Customer_ID, Total_Sales FROM ( SELECT Customer_ID, SUM(Sales) AS Total_Sales FROM Orders GROUP BY Customer_ID ) AS Customer_Sales WHERE Total_Sales > 100000;

Or using a CTE:

WITH Customer_Sales AS ( SELECT Customer_ID, SUM(Sales) AS Total_Sales FROM Orders GROUP BY Customer_ID ) SELECT Customer_ID, Total_Sales FROM Customer_Sales WHERE Total_Sales > 100000;

Both approaches produce the same analytical idea.

🧪 Practical Interview Challenge

Suppose you have Employees table

Q1. Find employees earning above the overall average.

SELECT Name, Salary FROM Employees WHERE Salary > ( SELECT AVG(Salary) FROM Employees );

Q2. Find employees earning above their department average.

SELECT e.Name, e.Department, e.Salary FROM Employees e WHERE e.Salary > ( SELECT AVG(e2.Salary) FROM Employees e2 WHERE e2.Department = e.Department );

Q3. Create a CTE containing average salary by department.

WITH Department_Salary AS ( SELECT Department, AVG(Salary) AS Average_Salary FROM Employees GROUP BY Department ) SELECT * FROM Department_Salary;

Q4. Find departments whose average salary exceeds ₹70,000.

WITH Department_Salary AS ( SELECT Department, AVG(Salary) AS Average_Salary FROM Employees GROUP BY Department )

SELECT Department, Average_Salary FROM Department_Salary WHERE Average_Salary > 70000;

Q5. Find customers who have placed at least one order.

SELECT c.Customer_ID, c.Customer_Name FROM Customers c WHERE EXISTS ( SELECT 1 FROM Orders o WHERE o.Customer_ID = c.Customer_ID );

🏆 Double Tap ❤️ For More

The CTE is often easier to read when the query becomes complex.

A good rule:

Simple calculation → subquery can be fine.

Multiple logical steps → CTE is often clearer.

1️⃣7️⃣ CTE vs Derived Table

Conceptually, both can create an intermediate result.

Derived Table: Usually appears inside: FROM (...)

CTE: Defined before the main query: WITH Name AS (...)

CTEs generally make multi-step analytical queries easier to organize.

1️⃣8️⃣ CTE for Data Filtering

Suppose you only want 2026 orders.

WITH Orders_2026 AS ( SELECT * FROM Orders WHERE Order_Date >= '2026-01-01' AND Order_Date < '2027-01-01' )

SELECT Region, SUM(Sales) AS Total_Sales FROM Orders_2026 GROUP BY Region;

This makes the query's logic easy to follow:

First → select 2026, Then → analyze by region

1️⃣9️⃣ CTE for Business Logic

Suppose you want to classify orders:

WITH Classified_Orders AS ( SELECT Order_ID, Sales, CASE WHEN Sales >= 100000 THEN 'High' WHEN Sales >= 50000 THEN 'Medium' ELSE 'Low' END AS Sales_Category FROM Orders )

SELECT Sales_Category, COUNT(*) AS Order_Count FROM Classified_Orders GROUP BY Sales_Category;

Now you've separated: Classification from: Aggregation. This is much easier to maintain.

2️⃣0️⃣ CTE for Multi-Step Analysis

Imagine the business asks:

Which region has the highest average customer sales?

A CTE can break this into understandable stages.

For example:

WITH Customer_Sales AS ( SELECT Customer_ID, SUM(Sales) AS Total_Sales FROM Orders GROUP BY Customer_ID ), Regional_Customer_Sales AS ( SELECT c.Region, cs.Customer_ID, cs.Total_Sales FROM Customer_Sales cs JOIN Customers c ON cs.Customer_ID = c.Customer_ID )

SELECT Region, AVG(Total_Sales) AS Avg_Customer_Sales FROM Regional_Customer_Sales GROUP BY Region ORDER BY Avg_Customer_Sales DESC;

This is much easier to reason about than attempting everything at once.

2️⃣1️⃣ CTEs Are Not Permanent Tables

This is important.

A normal table: Customers, Orders, Products is stored in the database.

A CTE: WITH Customer_Sales AS (...) exists only for the duration of that query.

2️⃣2️⃣ CTEs and Performance

A common misconception is:

"CTEs are always faster than subqueries."

That's not necessarily true.

A CTE is primarily a query organization/readability tool.

Actual performance depends on: Database engine, Query structure, Indexes, Data volume, Optimizer behavior, Joins, Aggregations

So don't use a CTE simply because you think it automatically makes a query faster. Use it when it makes the logic clearer or otherwise fits your query design.

2️⃣3️⃣ Correlated Subquery

A correlated subquery references a column from the outer query.

Example:

SELECT e.Name, e.Salary FROM Employees e WHERE e.Salary > ( SELECT AVG(e2.Salary) FROM Employees e2 WHERE e2.Department = e.Department );

📊 6 Aplicaciones Actualizadas  el 1 de Septiembre 🔄  🚨

✔️ Recuerda visitarnos todos los días tenemos contenido para disfrutar totalmente gratis.

✔️ Para ver las aplicaciones que compartimos deben instalar la tienda WEB-TOOLS:

Link official web 💳 apkdescargas.com

Link official telegram 💳 t.me/+PEeV1ZzS4K5hYTFh

❤️‍🔥Si ya tienes instalada la tienda WEB TOOLS ingresa a ella, todos los días tenemos aplicaciones disponibles para que disfruten de esas apps totalmente gratis.

Dejen sus ❤️ y Compartan esta publicación para ayudar a crecer y fortalecer esta comunidad de aplicaciones. 🤝🏻

GRM Tokenomics Update Notice

​We are excited to share an important update regarding our token economics as we approach our confirmed 2026 TGE. To better support the growth and expansion of our ecosystem, our total fixed supply has increased.

​Below is the updated token distribution breakdown for $GRM:

​Token Name: GRM Total Fixed Supply: 1,000,000,000 $GRM

TGE: 2026 Confirmed

Mining Community: 44% (440,000,000 GRM)

Listing Price: 0.09+ USDT

Link: https://telegram.me/Gramnetwork_bot?startapp=571980418

ВРЕМЯ ТОТАЛЬНОГО ФЕЙКА

На площадь покрытия зон

Срочно делаем ставки.

Время пакетов «Озон».

Время «Яндекс Доставки».

Всем длинным текстам фальстарт,

Фраза должна быть краткой.

Время натальных карт.

Время дыхания маткой.

Лень победила всех.

Таксистов больше, чем прачек.

Время вебкамных утех.

Время китайских тачек.

Счастливо может жить

Только в рекламе семейка.

Время «В Питере пить».

Время тотального фейка.

Ieri ti ho condiviso i 7 segnali. Ma riconoscere un problema non significa ancora averlo trasformato. Puoi capire che la mente è sovraccarica. Puoi accorgerti che il corpo è trascurato. Puoi vedere che la tua attenzione viene dispersa continuamente. Ma poi rimane una domanda: “Da dove comincio?” È proprio da questa domanda che nasce Rigenerazione Totale. Il libro segue un ordine molto semplice: CORPO → MENTE → ENERGIA Prima lavori sulle fondamenta fisiche. Poi inizi a riportare ordine nella mente e nell’attenzione. Infine impari a dirigere meglio la tua energia verso ciò che conta davvero.

Se la guida gratuita ti ha fatto riconoscere qualcosa di te, Rigenerazione Totale è il passo successivo.

📖 Puoi vedere il libro su Amazon qui: https://www.amazon.it/dp/B0HH9VG818

Всем привет! 🧡

Заканчиваем серию постов про сложные SQL-группировки, и на очереди - CROUPING SETS.

GROUPING SETS - выборочная группировка ✉️

Когда полезен ⚡️ Когда отсутствует единый паттерн группировки, и пользователь хочет настроить ее гибко: в таком случае использование ROLLUP малополезно (пользователю может быть не нужна иерархия), а CUBE - избыточно (зачем все комбинации, если нужна всего одна или две?). В таком случае GROUPING SETS и становится лучшим выбором.

Пример 📚 Допустим, у нас есть все та же таблица grouping со следующим набором данных: | year | month | day | total | |------|-------|-----|-------| | 2025 | 1| 1| 200| | 2025 | 1| 1| 130| | 2025 | 1| 2| 100| | 2025 | 2| 1| 900| | 2026 | 11| 13| 60|

Требуется написать запрос, который выведет суммарную прибыль с группировкой по числам и по месяцам разных лет (без учета дней).

В таком случае ROLLUP нам не поможет, так как он выведет информацию с группировкой по числам, по числам месяцев и по числам месяцев различных лет, что нам не требуется. Что касается CUBE, он выведет все возможные комбинации, среди которых будут и нужные, но большинство из них мы рассчитывать не планировали.

Запрос *️⃣ SELECT year, month, day, SUM(total) FROM grouping GROUP BY GROUPING SETS ( (day), (year, month) );

Результат ✉️ | year | month | day | total | |------|-------|-----|-------| | | | 13| 60| | | | 2| 100| | | | 1| 1230| | 2025 | 2| | 900| | 2026 | 11| | 60| | 2025 | 1| | 430|

Поскольку сортировка явно не задана, порядок строк выбран произвольно.

Какие из группировок (ROLLUP, CUBE, GROUPING SETS) вы знали до того, как мы опубликовали эту серию постов?

#SQL

🔠🔠🔠🔠🔠🔠🔠🔠🔠 GF wallet GAEJNNXAYFWSHTQOWCWCKCFCGILAMZMRLVFPRUQIIBUDWFRRXL3A3D7K

Issuer: GA5IJVFXOO3Q66IJP35JJLT5YCVXESHES5SUEJDPDJ4JUFTLZP5EID7O

Post 1 of 3

SAFEHAVEN

The Protection Ordinary Families Were Priced Out Of

Protection is one of the quietest advantages of wealth.

The wealthy do not only have more assets. They have better structures around those assets. Lawyers, trusts, estate plans, private custody, beneficiary rules, emergency instructions, professional advisers, and recovery procedures all exist to make sure one death, illness, dispute, or mistake does not destroy what a family has built.

Ordinary families often live without that shield.

A parent works for decades, but the family home can still become trapped in paperwork. Savings meant for a child can be delayed or contested. A disabled relative may need support, but the proper structure to protect them is too expensive. A widow may be forced to fight systems at the exact moment she needs help. A small business owner may build something real, but leave no clean path for continuity if something happens.

The problem is not lack of love.

It is lack of access.

The people who need protection most are often the people least able to afford it.

SAFEHAVEN begins from one principle:

protection should not be a privilege of wealth.

A family should be able to protect a home, provide for a child, support a dependent, leave instructions, and control how value moves during crisis without entering an expensive legal maze.

But protection has another danger.

The same structures that protect honest families can also hide abuse. Total secrecy can conceal ownership, disguise control, and make wrongdoing invisible. Total exposure can turn innocent families into targets.

Neither extreme is good enough.

SAFEHAVEN is built for the balance:

private people, accountable movement.

Identities can remain protected. But actions, conditions, distributions, and protected value movement should be verifiable. Privacy should defend the innocent. It should not create a shelter for the guilty.

This is where XLM becomes the rail.

Protection must move when life changes.

A death occurs. An emergency happens. A beneficiary becomes eligible. A dependent needs support. A recovery instruction activates. A protected payment must be released.

Old systems often move slowly when people need certainty most.

SAFEHAVEN creates a faster, clearer protection layer using XLM for beneficiary routing, emergency access, protected transfers, recovery rules, and transparent execution.

The purpose is not to replace care.

The purpose is to make care durable.

At TT, the first SAFEHAVEN protection route activates.

The first protected instruction becomes live.

The first founding class is recorded.

This event is called:

THE FIRST HAVEN OPENS

Those positioned before TT become:

HAVEN FOUNDERS

Later participants may use future protection routes.

But they cannot become the class that opened the original haven.

SAFEHAVEN

A shield for ordinary families.

Privacy for honest people.

Accountable movement through XLM.

At TT, protection stops belonging only to the wealthy.

Strategy telah melakukan pembelian Bitcoin pertamanya dalam dua bulan terakhir, dengan mengakuisisi 4.603 BTC senilai $369,7 juta pada harga rata-rata $80.318 per koin, menurut siaran pers perusahaan pada Senin pagi. Pembelian ini meningkatkan total kepemilikan Strategy menjadi 845.050 BTC sekaligus mengakhiri jeda aktivitas pembelian. Mekanisme transaksi ini tergolong sederhana. Strategy menjual saham biasa senilai $602,8 juta dan menggunakan $369,7 juta dari hasil penjualan tersebut untuk membeli 4.603 BTC tersebut.

Sisa dana hasil penjualan tersebut dialokasikan menjadi dua bagian: sebesar $151,8 juta digunakan untuk membeli kembali saham preferen STRC milik perusahaan, sementara sisanya menambah cadangan kas Strategy. Dengan pembelian terbaru ini, total biaya akuisisi Bitcoin Strategy mencapai sekitar $63,73 miliar, sehingga harga pembelian rata-rata historisnya berada di kisaran $75.412 per BTC.

Suas preocupações são politicamente totalmente compreensíveis. Esse fenômeno que você descreve – uma postura muito polida, retoricamente forte e 'limpa', que finge empatia social, mas que no fundo defende uma ideologia de mercado neoliberal que prejudica a classe trabalhadora – é conhecido no mundo inteiro. Isso lembra muito os partidos que colocam o livre mercado acima de tudo e transferem os problemas sociais principalmente para as costas do indivíduo.

Aqui está um texto em português que você pode enviar exatamente assim para o seu primo. Ele aborda o Cury de forma respeitosa como pessoa, mas expõe os mecanismos por trás da retórica:

------------------------------ Texto para o seu primo:

Olha, eu entendo perfeitamente por que muita gente está animada com o Augusto Cury G1. Ele fala muito bem, parece calmo, limpo, dominando a retórica, e usa palavras bonitas sobre o "coração social" e a saúde mental CNN Brasil. É uma imagem perfeita para parecer a "solução nova" que o Brasil tanto precisa.

Mas se você olhar por trás desse discurso bonito, vai ver que a ideologia dele é uma armadilha perigosa para o trabalhador e para o homem simples. É o famoso "capitalismo de palco" disfarçado de projeto social. Deixa eu te explicar o porquê com base no que ele mesmo defende:

1. A ilusão do "Você Consegue" (Coaching vs. Realidade): O Cury quer resolver a pobreza criando "escolas de empreendedorismo" e dando microcrédito Folha de S.Paulo. Na teoria parece lindo, mas na prática isso joga toda a culpa e a responsabilidade nas costas do trabalhador. É dizer para o motorista de aplicativo ou para a empregada doméstica: "Se você não vencer na vida, é porque você não controlou suas emoções ou não se esforçou". Isso ignora que o trabalhador precisa de salário justo, direitos e segurança, e não de palestra de autoajuda.

2. Livre Mercado Radical: Ele defende o livre mercado total, corte de ministérios e redução do papel do Estado na economia G1. Ele até elogiou o Paulo Guedes (ex-ministro da Economia) como uma "mente brilhante" CNN Brasil. Essa política de mercado sem freio é exatamente o que as elites querem: menos impostos para os milionários e menos proteção para quem está na base. É a mesma ideologia que na Europa destrói os direitos trabalhistas e privatiza o que é do povo.

3. Quem realmente lucra? O Cury declarou um patrimônio de 242 milhões de reais G1. Ele é o candidato mais rico da eleição Gazeta do Povo. Ele não vai taxar as grandes fortunas, não vai mexer nos privilégios dos super-ricos e nem na herança das elites. O plano dele mantém os ricos intocados lá no topo, enquanto oferece "gestão da emoção" para o pobre aguentar a crise com um sorriso no rosto.

Cuidado com essa propaganda muito limpa e profissional. Políticos que se posicionam como salvadores da pátria acima da esquerda e da direita, mas que só oferecem "livre mercado" e "esforço individual", historicamente governam para os ricos. Para o cidadão comum, isso não passa de uma armadilha retórica perigosa.

@ameninaveneno17

Q5. Find customers whose total sales exceed ₹50,000.

SELECT c.Customer_Name, SUM(o.Sales) AS Total_Sales FROM Customers c JOIN Orders o ON c.Customer_ID = o.Customer_ID GROUP BY c.Customer_Name HAVING SUM(o.Sales) > 50000;

🏆 Double Tap ❤️ For More

SELECT c.Customer_Name, o.Order_ID, p.Product_Name, o.Sales FROM Customers c JOIN Orders o ON c.Customer_ID = o.Customer_ID JOIN Products p ON o.Product_ID = p.Product_ID;

1️⃣5️⃣ Table Aliases

Customers c, Orders o, Products p

Instead of Customers.Customer_ID, you can write c.Customer_ID. Much easier to read.

1️⃣6️⃣ JOIN + GROUP BY

This is one of the most important patterns.

SELECT c.Customer_Name, SUM(o.Sales) AS Total_Sales FROM Customers c JOIN Orders o ON c.Customer_ID = o.Customer_ID GROUP BY c.Customer_Name;

JOIN + SUM + GROUP BY is a very common interview question.

1️⃣7️⃣ JOIN + WHERE

SELECT c.Customer_Name, o.Sales FROM Customers c JOIN Orders o ON c.Customer_ID = o.Customer_ID WHERE c.Department = 'IT';

JOIN connects, WHERE filters.

1️⃣8️⃣ JOIN + HAVING

SELECT c.Customer_Name, SUM(o.Sales) AS Total_Sales FROM Customers c JOIN Orders o ON c.Customer_ID = o.Customer_ID GROUP BY c.Customer_Name HAVING SUM(o.Sales) > 100000;

Pattern: JOIN → GROUP BY → SUM → HAVING

1️⃣9️⃣ The Most Important LEFT JOIN Pattern

SELECT c.Customer_ID, c.Customer_Name FROM Customers c LEFT JOIN Orders o ON c.Customer_ID = o.Customer_ID WHERE o.Customer_ID IS NULL;

Answers: Which customers have no orders?

General pattern: LEFT JOIN + WHERE right_table.key IS NULL

2️⃣0️⃣ JOIN and NULL

After a LEFT JOIN, unmatched columns become NULL. That NULL tells us: No matching order was found.

2️⃣1️⃣ Self JOIN

A Self JOIN joins a table to itself. Useful for employee-manager relationships.

SELECT e.Employee_Name AS Employee, m.Employee_Name AS Manager FROM Employees e LEFT JOIN Employees m ON e.Manager_ID = m.Employee_ID;

2️⃣2️⃣ Many-to-One Relationships

Customers → Orders is One-to-Many. From Orders perspective, it's Many-to-One. Understanding direction is critical.

2️⃣3️⃣ The Duplicate Row Problem

If John has 3 orders, after JOIN John appears 3 times. That's correct, not an error. Always understand relationship cardinality.

2️⃣4️⃣ JOIN Multiplication

If a customer has 3 orders and 4 payments, an incorrect join can produce 12 combinations and inflate Sales, Counts, Profit. Always check grain before aggregating.

2️⃣5️⃣ What Is Table Grain?

Grain means: What does one row represent?

Customers: One row = one customer

Orders: One row = one order

2️⃣6️⃣ JOIN vs UNION

• JOIN: Combines tables horizontally. Adds columns.

• UNION: Combines results vertically. Adds rows.

2️⃣7️⃣ Practical Business Example

Question: What is total sales by region?

SELECT c.Region, SUM(o.Sales) AS Total_Sales FROM Customers c JOIN Orders o ON c.Customer_ID = o.Customer_ID GROUP BY c.Region ORDER BY Total_Sales DESC;

🧪 Practical Interview Challenge

Q1. Show customer names with their orders.

SELECT c.Customer_Name, o.Order_ID, o.Sales FROM Customers c JOIN Orders o ON c.Customer_ID = o.Customer_ID;

Q2. Show all customers, including those without orders.

SELECT c.Customer_Name, o.Order_ID, o.Sales FROM Customers c LEFT JOIN Orders o ON c.Customer_ID = o.Customer_ID;

Q3. Find customers who have never ordered.

SELECT c.Customer_ID, c.Customer_Name FROM Customers c LEFT JOIN Orders o ON c.Customer_ID = o.Customer_ID WHERE o.Customer_ID IS NULL;

Q4. Find total sales per customer.

SELECT c.Customer_Name, SUM(o.Sales) AS Total_Sales FROM Customers c JOIN Orders o ON c.Customer_ID = o.Customer_ID GROUP BY c.Customer_Name;