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I applied via campus placement at Osmania University and was interviewed in Nov 2022. There were 3 interview rounds.
It involves more of aptitute and reasoning questions
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I applied via Company Website and was interviewed before Apr 2021. There were 3 interview rounds.
Data modeling is the process of creating a visual representation of data structures and relationships in a database.
Data modeling involves identifying entities, attributes, and relationships.
It helps in organizing data in a way that is easy to understand and analyze.
Examples of data modeling tools include ER diagrams, UML diagrams, and data flow diagrams.
I applied via Walk-in and was interviewed in Nov 2024. There was 1 interview round.
Create a flag to identify data that has not been updated
Add a new column in the dataset called 'Updated Flag'
Use a formula to check if the data has been updated recently
For example, if the last update date is more than 30 days ago, set the flag to 'Not Updated'
I applied via Approached by Company and was interviewed in Mar 2024. There were 2 interview rounds.
I was interviewed in Feb 2024.
Rank assigns unique ranks to each row, while dense rank assigns consecutive ranks without gaps.
Rank leaves gaps in rank numbers if there are ties, while dense rank does not
Rank function is non-consecutive, while dense rank function is consecutive
Rank function can skip numbers, while dense rank function does not
posted on 10 Apr 2024
I applied via Job Portal and was interviewed in Mar 2024. There was 1 interview round.
LODS (Level of Detail Expressions) and rank functions are used in Tableau for advanced calculations and analysis.
LODS allow you to control the level of detail in your visualization by specifying the dimensions at which you want to aggregate data.
Rank functions like RANK(), DENSE_RANK(), and ROW_NUMBER() are used to assign a rank to each row of data based on a specified criteria.
LODS and rank functions can be used toget...
Basic Level questions about Tableau
Types of LODs in Tableau include Fixed, Include, and Exclude.
Fixed LOD: Computes a value using specified dimensions, regardless of the visualization level.
Include LOD: Computes a value at a specified level of detail, including dimensions not in the visualization.
Exclude LOD: Computes a value at a specified level of detail, excluding dimensions not in the visualization.
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