Dell
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An inactive relationship in Power BI is a relationship that is not being used in any visualizations or calculations.
Inactive relationships can occur when a relationship is created but not utilized in any measures or visuals.
These relationships do not impact the data model or query performance, but can clutter the model view.
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Ina...
Import vs Direct Query vs Live connection
Import: Data is imported into the tool for analysis, suitable for small datasets or when real-time data is not required
Direct Query: Data is queried directly from the source in real-time, suitable for large datasets or when up-to-date data is needed
Live connection: Data is connected live to the source, allowing for real-time updates and analysis without storing data locally
I applied via LinkedIn and was interviewed in Apr 2024. There were 2 interview rounds.
I am a dedicated and detail-oriented analyst with a strong background in data analysis and problem-solving.
I have a Bachelor's degree in Statistics and have completed multiple data analysis projects during my studies.
I am proficient in using statistical software such as R and Python for data analysis.
I have experience in conducting market research and creating reports to help businesses make informed decisions.
I am a q...
The sales growth between the years is calculated by comparing the sales figures from one year to another.
Calculate the difference in sales between the two years
Divide the difference by the sales figure of the initial year
Multiply the result by 100 to get the percentage growth
For example, if sales were $100 in year 1 and $120 in year 2, the growth would be (120-100)/100 * 100 = 20%
I applied via Walk-in and was interviewed before Jan 2021. There were 3 interview rounds.
I applied via LinkedIn and was interviewed before Dec 2022. There were 3 interview rounds.
1 hour baisc on general aptitude
I applied via Recruitment Consulltant and was interviewed in Jun 2024. There were 2 interview rounds.
Developed a predictive analytics model to forecast customer churn for a telecom company
Used Python and SQL to clean and analyze customer data
Implemented machine learning algorithms such as logistic regression and random forest
Evaluated model performance using metrics like accuracy, precision, and recall
I have experience in time series forecasting using statistical models and machine learning algorithms.
Utilized ARIMA model to forecast sales data for a retail company
Implemented Prophet algorithm to predict stock prices for a financial institution
Used LSTM neural network for demand forecasting in supply chain management
Excel assessment- was made to make a report from multiple sheets
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