1. SAP HANA Real time
Data Analytics
PRESENTED BY: ALI ASAD, ANKITA BANERJEE, ISRAA TOLSON
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2.  Introduction of logistics and old method
 Case study DHL Last mile delivery
 Dimension and measures
 Star Schema – Prototype
 Data Models
 Views
 Analysis
 Conclusion
 Benefits
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3. Introduction of logistics
 Logistics is the process of planning , implementing and controlling the efficient
effective flow and storage of goods and related information from point of origin to
point of consumption for the purpose of meeting customer requirements.
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4. Previous Methods
• Previously, Sales order was created. Incase
of DHL, as soon as the package arrives at
destination Delivery order was created.
• While creating Delivery order, We put a
time & date on Point of delivery.
• Those date and time was the only way that
can be used to ensure whether the
package has been delivered successfully.
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http://www.kinaxis.com/en/solution/sales-and-operations-planning/

5. Case Study – DHL Last Mile Delivery 5
• With the final part of the delivery journey (the so-called “last mile”) being highly dependent on
Vehicles and Drivers, and as consumer demands become more sophisticated and delivery points
continue to multiply, logistics providers face new challenges.
• Lets consider Baden Württemberg as an example. There would be 10 Vehicles for example with
10 different drivers. One fine morning, one of the driver is sick, and one vehicle has some
mechanical problem.
• Data about these two situations should be instantly available to central office so that they can
assure timely arrival of couriers to respective customers by re-routing working vehicles and
drivers.
• This topic will further be presented during our project and you will see real time update of such
data to SAP Dashboards based on SAP Lumira.

6. Dimensions
 For our analysis , the following dimension are used:
 TIME
 DRIVER
 VEHICLE
 ROUTE
 The measures were:
 The vehicle status
 The driver’s health status
 Route Distance in Km.
 Other Restricted columns were also used as Measures.
Tables and views were created using SAP Hana studio on Eclipse and analysis was
done in SAP Lumira
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7. Star Schema - Prototype 7

8. Data Models – SAP HANA 8
 Driver Master data table with driver ID as
key figure.
 Time Master data table, that was not
taken from time dimension. Because
Standard table had no data, and there
were lot more attributes, that did not add
value if corresponding data was
generated.

9. Data Models – SAP HANA 9
 Vehicle Master data that has Vehicle_id as
the primary key.
 Region Master data with region_id as the
primary key.

10. Data Models – SAP HANA 10
 Transaction data for DHL Real time
Analytics with primary-foreign key
relationship and three measures namely;
1. Vehicle Status – having values between 0
and 5. Range between 3 – 5 is considered
as safe status. And range between 0-3 is
unsafe.
2. Driver Health Status, 0 means sick, and 1
means healthy.
3. Route distance mentioned in Km.

11. Attribute views
DRIVER TIME
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REGION VEHICLE

12. Analytic view 12

13. 13
 There were three measures in our fact
table, but in order to make our
analysis more detailed, we have
added 6 more restricted columns as
measures.
Analytic View: Restricted Columns as Measures.

14. Analysis 14

15. Analysis 15

16. Analysis 16

17. Analysis 17

18. Conclusion
 Dashboards that have been presented, clearly shows several measures in
comparison to dimensions on different types of graphs.
 Those can be used, by control centre operator to make sure that efficiently
functioning vehicles are driven on long routes, keeping driver’s health
status in perspective.
 These dashboards need to be studied, together in order to come to
conclusion, because several measures against several dimensions on the
same chart is not possible.
 We believe, that this data model can further be extended to include all of
Deutschland, and then geographic graphs can also be utilized providing
more insights to real time analysis.
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19. Benefits of SAP HANA for logistic 19
 Provide timely delivery information to support more intelligent decisions around scheduling and
order fulfillment.
 Use real-time information to make adjustments to modify delivery options.
 Simplify system administration and IT operations with tools that help you monitor processes, ensure
data and application security, and achieve continuous availability.
 Since SAP S/4HANA uses a new data model, aggregates and indices are no longer necessary, so
significantly less memory space is required than with conventional database management systems.

20. Thank You for listening patiently.
We are open to your Question.
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