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SQL rank order function explanation
Rank order function in SQL assigns a rank to each row based on a specified column
It can be used to determine the top or bottom N records in a dataset
Example: SELECT column1, column2, RANK() OVER (ORDER BY column3 DESC) AS rank_order FROM table_name
Merging two tables involves combining data from both tables based on a common key.
Identify a common key between the two tables
Use SQL JOIN statements to merge the tables
Choose the appropriate type of join (e.g. inner join, outer join)
Consider the size of the tables and the performance implications of the merge
Data is a collection of facts, figures, or statistics that can be analyzed to gain insights and make informed decisions.
Data can be structured or unstructured
Data can be qualitative or quantitative
Examples of data include customer demographics, sales figures, and website traffic
Data can be analyzed using various tools and techniques to extract meaningful insights
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.
To remove an inactive relationship, you can delete it from the relationship view in Power BI.
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
Skil set for My relevant job update
Communication discussion
I rate myself 8/10 in Advanced Excel and 9/10 in SQL.
Advanced Excel: proficient in pivot tables, VLOOKUP, macros, and data visualization
SQL: skilled in writing complex queries, joins, subqueries, and stored procedures
Experience in using Excel and SQL together to analyze large datasets
To work with dynamic data, remove duplicates and fix errors, use data cleaning techniques.
Use software tools like OpenRefine or Excel to clean data
Identify and remove duplicate data using unique identifiers
Fix errors by standardizing data formats and using regular expressions
Use data validation to ensure accuracy and completeness
Create a data cleaning plan and document all changes made
Test the cleaned data to ensure it
Formula is a mathematical expression while function is a pre-built formula that performs a specific task.
Formula is a combination of mathematical operators and values used to calculate a result.
Function is a pre-built formula that performs a specific task, such as finding the average of a range of numbers.
Formulas can be customized and modified, while functions are fixed and cannot be changed.
Examples of functions incl
I applied via Walk-in and was interviewed in Mar 2024. There was 1 interview round.
I am a data analyst with 5 years of experience in analyzing and interpreting complex data sets to drive business decisions.
I have a strong background in statistical analysis and data visualization techniques.
Proficient in SQL, Python, and Tableau for data manipulation and reporting.
Experience in developing predictive models and conducting A/B testing to optimize marketing strategies.
I applied via LinkedIn and was interviewed before Apr 2022. There were 2 interview rounds.
The diagonals AC and BD of a cyclic quadrilateral ABCD intersect each other at the point P. Then, it is always true that
It was not easy only people can clear who are better in pandas and numpy
I applied via Naukri.com and was interviewed in Apr 2024. There were 2 interview rounds.
Dsa questions in java questions- dynamic programming
I expect a challenging role where I can utilize my analytical skills to solve complex problems and contribute to the success of the organization.
Opportunity to work with large datasets and use statistical analysis to derive insights
Collaboration with cross-functional teams to drive data-driven decision making
Continuous learning and professional development opportunities
Clear communication of findings and recommendation
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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