Power BI End to End Project ( Banking Domain) 

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​@@KSRDatavizon mam can you provide total deccription too

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Nice bro good and Easy idea i got result through yours simple way DAX.

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Thank you for the suggestion! We'll definitely consider creating an end-to-end project video on supply chain solutions.

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@@KSRDatavizon ok thnks. I m doing internship now but we hv don't know abt projexlct and i saw your videos and i hav done your project bank domain so pls giv us one more project pls

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Facing the same problem.I hope you found the solution. Please help if you got the solution.

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sure, will make those video shortly . than you.

Understanding the Issue: It seems you're encountering an error when attempting to convert the "Bank DOJ" column from text to date or date/time format in Power Query. This typically occurs when the text data is in an inconsistent or unrecognized format. Troubleshooting Steps: Inspect the Data: Check for Inconsistencies: Ensure that all values in the "Bank DOJ" column are formatted consistently (e.g., "DD/MM/YYYY", "MM/DD/YYYY"). Identify Invalid Dates: Look for any entries that might contain invalid dates (e.g., incorrect day, month, or year). Remove Extra Characters: If there are any extraneous characters (e.g., spaces, hyphens) surrounding the date, remove them using Power Query's text functions. Adjust the Data Type: Choose the Correct Format: Select the appropriate data type (date or date/time) based on the format of your data. Specify the Format: If your data is in a non-standard format, you might need to use the Text.Format function to specify the correct format. For example, if your data is in "DD/MM/YYYY" format, you could use: Code snippet Text.Format([Bank DOJ], "DD/MM/YYYY") Use code with caution. Handle Errors: Use try...otherwise: If there are invalid dates in your data, you can use the try...otherwise function to handle errors gracefully. For example: Code snippet try Text.Format([Bank DOJ], "DD/MM/YYYY") otherwise null Use code with caution. Filter Out Errors: You can also filter out rows with invalid dates using the Table.SelectRows function. Example Power Query Formula: Code snippet let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("dZAAAAAAAAgEAAAD/AAAA/gAAAAAAAAA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = #table({"Bank DOJ"}, {{"01/01/2024"}}) in _t), #"Changed to Text" = Table.TransformColumns(Source, {{"Bank DOJ", Text.Type}}), #"Filtered for Errors" = Table.SelectRows(#"Changed to Text", each try Text.Format([Bank DOJ], "DD/MM/YYYY") otherwise null null), #"Added Custom Column" = Table.AddColumn(#"Filtered for Errors", "Bank DOJ (Date)", each try Date.FromText([Bank DOJ], "DD/MM/YYYY") otherwise null) in #"Added Custom Column" Use code with caution. This example assumes your data is in "DD/MM/YYYY" format. Adjust the format as needed based on your specific data. Additional Tips: If your data contains time information, you'll need to use the appropriate date/time format (e.g., "DD/MM/YYYY HH:MM:SS"). Consider using Power Query's built-in date/time functions (e.g., Date.FromText, Time.FromText) to simplify your transformations. If you're still encountering issues, provide more details about your data (e.g., sample values, expected format) for more tailored assistance. By following these steps and carefully inspecting your data, you should be able to successfully convert the "Bank DOJ" column to the desired date or date/time format in Power Query.

pls post your measure calculation here.. there could be filter context error

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Bcoz same Column name. as they used fact table "Date Column" if you remember.

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yes , you can add in your resume, but chnage the clients name

Sure mam will do asap

we can do either way sir.. each biz defines own way of churn

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@@KSRDatavizon could you plz make video on manage parameters .

Yes, soon

Converting Mixed-Format Dates in Power Query Understanding the Problem: When importing CSV data into Power Query, it's common to encounter mixed date formats, especially when the data source isn't consistent. This can lead to errors when attempting to convert the data to a date data type. Solution: Identify the Formats: Use the Text.Format function to inspect the first few rows and identify the distinct date formats present. For example: Code snippet Table.TransformColumns(YourTable, {"DateColumn"}, each Text.Format(_, "yyyy-mm-dd")) Use code with caution. Replace "yyyy-mm-dd" with the appropriate format based on your data. Create a Custom Function: If you have multiple formats or complex logic, create a custom function to handle the conversion: Code snippet let ConvertDate = (dateText as text) as datetime => if Text.StartsWith(dateText, "MM/DD/YYYY") then DateTime.FromText(dateText, "MM/DD/YYYY") else if Text.StartsWith(dateText, "DD/MM/YYYY") then DateTime.FromText(dateText, "DD/MM/YYYY") else DateTime.FromText(dateText, "YYYY-MM-DD") in ConvertDate Use code with caution. Apply the Function: Use the Table.TransformColumns function to apply the custom function to the date column: Code snippet Table.TransformColumns(YourTable, {"DateColumn"}, each ConvertDate(_)) Use code with caution. Example: Assuming your date column is named "Date" and has formats like "MM/DD/YYYY" and "DD/MM/YYYY", you could use the following code: Code snippet let Source = Csv.Document(File.Contents("YourFile.csv"), [Delimiter=","]), #"Changed Type" = Table.TransformColumns(Source, {"Date"}, each try DateTime.FromText(_, "MM/DD/YYYY") otherwise DateTime.FromText(_, "DD/MM/YYYY")), #"Filtered Rows" = Table.SelectRows(#"Changed Type", each not IsError([Date])) in #"Filtered Rows" Use code with caution. Additional Tips: If you're unsure about the formats, you can use the Text.Format function to experiment with different formats until you find the correct ones. For more complex scenarios, you might need to use regular expressions or other advanced techniques. Consider using conditional logic or custom functions to handle edge cases or specific requirements. By following these steps, you should be able to successfully convert mixed-format dates in Power Query and avoid errors.