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SAP Lumira
Acquiring Data
Acquire a dataset
2
SAP Lumira allows to acquire data from different sources such as:
• SAP HANA analytic view (an in-memory, column-oriented, relational database
management system)
• Microsoft Excel file with multiple worksheets
• Universe
• You will be required to enter the credentials for the Business Intelligence platform
where your universe is stored
• Freehand SQL
• You must first have downloaded the .jar files for the drivers from the website for the
appropriate database type
• Than navigate to File -> Preferences -> SQL Drivers to install the drivers
When connecting to a new data source you can either create a new document or
add a new dataset within an existing document
Acquire a dataset from a universe
3
• After entering the credentials for the BI platform you
should choose the universe and name your dataset
• A universe tree displays the available objects in the
universe, which you can select to acquire
• If desired, you can include a universe level filter or prompt
• Filters restrict data to include only the specified results
• Prompts enable you to specify results by typing one or
more values or selecting values from a list
• You can choose to preview the data before acquiring the
dataset, which enables you to apply additional filters
• If required, you can also change the query properties such
as the size of the query or the maximum retrieval time
• When previewing the values, you can apply filters directly
to the column
Combine datasets
4
SAP Lumira allows to combine datasets in two ways:
• By appending records if the two datasets have the same structure
• To append datasets you should use Combine as -> Append in
the Prepare workspace
• By merging on a shared column
• To merge datasets you should use Combine as -> Merge in
the Prepare workspace
SAP Lumira allows to append existing datasets as long as to create a
new dataset while appending
Combine datasets. Appending.
5
o Using the eFashion universe create two datasets with the next set of columns:
Year, City, Lines, Sales revenue. The first dataset should contain the Line
“Trousers” and the second – “City Trousers”. This should be done by using the
universe prompt “Prompt for a line item?”
o Append the two datasets
Combine datasets. Merging.
6
o Using the eFashion universe create the dataset which contains
the next fields: State and Sales revenue. Enable preview of the
data and exclude DC state using preview filters
o Create the second dataset using the eStaff universe. Include the
next fields: State and Quantity sold. Exclude the same state as
for the first dataset
o Match the two datasets on the State column
The result should look like this:
Manage connections
7
From the side bar you can access the connection page which you can
use to view and edit all the connections defined between documents
and data sources
• If you have a long list of datasets, you can use the search feature to
find specific datasets by name
• You can modify the connection to point to a new data source
provided the new source has the same structure as the original
source

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SAP Lumira - Acquiring data

  • 2. Acquire a dataset 2 SAP Lumira allows to acquire data from different sources such as: • SAP HANA analytic view (an in-memory, column-oriented, relational database management system) • Microsoft Excel file with multiple worksheets • Universe • You will be required to enter the credentials for the Business Intelligence platform where your universe is stored • Freehand SQL • You must first have downloaded the .jar files for the drivers from the website for the appropriate database type • Than navigate to File -> Preferences -> SQL Drivers to install the drivers When connecting to a new data source you can either create a new document or add a new dataset within an existing document
  • 3. Acquire a dataset from a universe 3 • After entering the credentials for the BI platform you should choose the universe and name your dataset • A universe tree displays the available objects in the universe, which you can select to acquire • If desired, you can include a universe level filter or prompt • Filters restrict data to include only the specified results • Prompts enable you to specify results by typing one or more values or selecting values from a list • You can choose to preview the data before acquiring the dataset, which enables you to apply additional filters • If required, you can also change the query properties such as the size of the query or the maximum retrieval time • When previewing the values, you can apply filters directly to the column
  • 4. Combine datasets 4 SAP Lumira allows to combine datasets in two ways: • By appending records if the two datasets have the same structure • To append datasets you should use Combine as -> Append in the Prepare workspace • By merging on a shared column • To merge datasets you should use Combine as -> Merge in the Prepare workspace SAP Lumira allows to append existing datasets as long as to create a new dataset while appending
  • 5. Combine datasets. Appending. 5 o Using the eFashion universe create two datasets with the next set of columns: Year, City, Lines, Sales revenue. The first dataset should contain the Line “Trousers” and the second – “City Trousers”. This should be done by using the universe prompt “Prompt for a line item?” o Append the two datasets
  • 6. Combine datasets. Merging. 6 o Using the eFashion universe create the dataset which contains the next fields: State and Sales revenue. Enable preview of the data and exclude DC state using preview filters o Create the second dataset using the eStaff universe. Include the next fields: State and Quantity sold. Exclude the same state as for the first dataset o Match the two datasets on the State column The result should look like this:
  • 7. Manage connections 7 From the side bar you can access the connection page which you can use to view and edit all the connections defined between documents and data sources • If you have a long list of datasets, you can use the search feature to find specific datasets by name • You can modify the connection to point to a new data source provided the new source has the same structure as the original source