Hi @Cosmin - Please find the solution from Data Mentor. Do check.
Thanks
Ankit J
Problem Analysis
You have two tables:
- Table A: Contains employee data.
- Table B: Contains employee-related target information.
There is a relationship between these tables based on the Employee_ID
key. The goal is to analyze or combine these tables efficiently to derive meaningful insights.
Solution Overview
To effectively analyze the data from both tables, you need to:
- Establish a Relationship: Ensure that the relationship between the tables on
Employee_ID
is correctly defined.
- Perform Data Integration: Merge or join the data based on the
Employee_ID
to create a combined dataset for analysis.
- Analyze the Combined Data: Perform the necessary analysis based on the combined data, such as calculating performance metrics or deriving insights.
Below is a step-by-step guide, assuming you are using a tool that supports SQL or Power Query (DAX).
Power Query (M Language)
If you are using Power Query in tools like Power BI or Excel, you can use the following steps:
// Language: M
let
// Load the tables
Employees = Excel.CurrentWorkbook(){[Name="Employees"]}[Content],
EmployeeTargets = Excel.CurrentWorkbook(){[Name="EmployeeTargets"]}[Content],
// Merge the tables based on Employee_ID
MergedTables = Table.NestedJoin(Employees, "Employee_ID", EmployeeTargets, "Employee_ID", "EmployeeTargets", JoinKind.Inner),
// Expand the merged columns
ExpandedTables = Table.ExpandTableColumn(MergedTables, "EmployeeTargets", {"Target", "Achievement"})
in
ExpandedTables
DAX Example
You can also create a relationship and then use DAX measures to analyze:
// Language: DAX
// Creating a calculated table if necessary
CombinedTable =
NATURALINNERJOIN(
Employees,
EmployeeTargets
)
// Example measure to calculate Total Achievement
TotalAchievement = SUM(CombinedTable[Achievement])
Best Practices
- Data Consistency: Ensure that
Employee_ID
values are consistent and unique across both tables.
- Data Cleansing: If necessary, clean the data to remove duplicates and handle missing values.
- Performance Optimization: Use appropriate joins and avoid unnecessary calculations to improve performance.
- Documentation: Properly document your analysis process and steps for future reference.
Conclusion
By following these steps, you can efficiently combine and analyze data from both tables. Using the provided SQL, Power Query, or DAX examples, you can tailor the solution to fit the specific analytics tool you are using. For a deeper understanding of such practices, consider exploring courses on the Enterprise DNA Platform.