Data Analytics
Perfect channel to learn Data Analytics Learn SQL, Python, Alteryx, Tableau, Power BI and many more For Promotions: @coderfun @love_data
Mostrar más📈 Análisis del canal de Telegram Data Analytics
El canal Data Analytics (@sqlspecialist) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 110 744 suscriptores, ocupando la posición 1 082 en la categoría Tecnologías y Aplicaciones y el puesto 2 206 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 110 744 suscriptores.
Según los últimos datos del 25 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -102, y en las últimas 24 horas de -15, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.99%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.27% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 3 314 visualizaciones. En el primer día suele acumular 1 405 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 6.
- Intereses temáticos: El contenido se centra en temas clave como row, sql, analytic, analyst, visualization.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Perfect channel to learn Data Analytics
Learn SQL, Python, Alteryx, Tableau, Power BI and many more
For Promotions: @coderfun @love_data”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 26 octubre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
Profit = Sales[Revenue] - Sales[Cost]
A measure could be:
Total Sales = SUM(Sales[SalesAmount])
I generally prefer measures for aggregations and KPI calculations because they respond dynamically to report filters.
🔟 What is DAX in Power BI?
Sample Answer:
DAX stands for Data Analysis Expressions. It is the formula language used in Power BI to create measures, calculated columns, and calculated tables.
For example:
Total Sales = SUM(Sales[SalesAmount])
Another example:
Profit Margin =
DIVIDE([Total Profit], [Total Sales], 0)
DAX is especially useful for business calculations such as KPIs, percentages, rankings, time intelligence, and comparisons.
📌 Double tap ❤️ for more.Total Sales =
SUM(Sales[Sales Amount])
Sales % of Total =
DIVIDE(
[Total Sales],
CALCULATE(
[Total Sales],
REMOVEFILTERS(Product)
)
)
“This allows the numerator to respond to the current product context while the denominator represents the overall total across products.”
📌 Double Tap ❤️ For More
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1.34 ₽ · /balance_helpIndia Sales =
CALCULATE(
[Total Sales],
Customer[Country] = "India"
)
CALCULATE() is fundamental for creating conditional and context-aware measures.”
2️⃣ What is the difference between SUM() and SUMX()?
Sample Answer:
“SUM() adds the values of a single column.
SUMX() is an iterator. It evaluates an expression row by row and then sums the results.
For example, if revenue needs to be calculated as Quantity multiplied by Price:
Total Revenue =
SUMX(
Sales,
Sales[Quantity] * Sales[Price]
)
I would use SUMX when the calculation needs to be performed for each row before aggregation.”
3️⃣ What is the difference between ALL() and REMOVEFILTERS()?
Sample Answer:
“Both can be used to remove filters in DAX.
REMOVEFILTERS() is specifically designed to remove filters and is generally clearer when that is the intended purpose.
For example, to calculate a percentage of total sales:
Sales % =
DIVIDE(
[Total Sales],
CALCULATE(
[Total Sales],
REMOVEFILTERS(Product)
)
)Sales Fact
↓
Customer Dimension
Product Dimension
Date Dimension
Region Dimension
The fact table contains measurable business events, while dimensions provide the context for analyzing those events.
A well-designed star schema generally makes Power BI models easier to understand and can improve performance.”
9️⃣ What is filter context in Power BI?
Sample Answer:
“Filter context is the set of filters that determines which data is considered when a DAX measure is evaluated.
For example, if I have a Total Sales measure and select ‘India’ in a Region slicer, the measure is evaluated only for the data remaining in that filter context.
Understanding filter context is essential for writing effective DAX measures.”
🔟 What is the difference between a report and a dashboard in Power BI?
Sample Answer:
“A report is generally a multi-page interactive analysis containing visuals, filters, slicers, and detailed information.
A dashboard is a single-page view in the Power BI Service that can contain tiles pinned from reports or other sources.
Reports are typically used for detailed analysis, while dashboards are often used to provide a high-level overview of important KPIs.”
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1.41 ₽ · /balance_helpTotal Sales = SUM(Sales[Sales Amount])
DAX becomes particularly powerful when calculations need to respond dynamically to filters and the report's filter context.”
5️⃣ What is the difference between a measure and a calculated column?
Sample Answer:
“A calculated column is calculated row by row and stored in the model.
A measure is calculated when it is used in a visual and responds to the current filter context.
For example, if I need a row-level calculation such as:
Profit = Sales[Revenue] - Sales[Cost]
a calculated column might be appropriate.
But for a KPI such as total profit:
Total Profit = SUM(Sales[Profit])
I would generally use a measure.”
6️⃣ What is a relationship in Power BI?
Sample Answer:
“A relationship connects tables using related columns.
For example, a Sales table may contain Product_ID and a Product table may also contain Product_ID. The relationship allows fields from the Product table to filter and analyze the Sales table.
Creating relationships correctly is critical because incorrect relationships can produce incorrect report results.”
7️⃣ What is the difference between a fact table and a dimension table?
Sample Answer:
“A fact table generally contains transactional or measurable business events, such as sales, orders, or transactions.
A dimension table contains descriptive information used to analyze those events, such as Customer, Product, Region, or Date.
For example:
Fact table → Sales
Dimension tables → Customer, Product, Date, Region
This structure makes the data model easier to analyze and maintain.”
8️⃣ What is a star schema?
Sample Answer:
“A star schema is a data modeling approach where a central fact table is connected to multiple dimension tables.
For example:=TODAY()-Last_Purchase_Date