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DWC Intelligent Lookup

Definition DWC Intelligent Lookup

When building complex data models in the Data Warehouse Cloud, data from different sources such as the DWC Data Marketplace are consulted.

The next step in harmonising this data is largely automated thanks to the Intelligent Lookup function: Instead of making formal adjustments, users can determine the extent to which they want to manually intervene in the data integration process. As a result, users are able to independently carry out and verify comprehensive steps for the extension of an existing data model, even without prior technical knowledge.

Case study Covid-19 and commodity prices 

In our other Wiki article on the topic DWC Data Marketplace already demonstrates data import using data on commodity prices and global Covid-19 caseloads. 

How do I apply the DWC Intelligent Lookup?

This example is now supplemented by the step of data preparation and visualisation. The comparison of two imported tables requires the alignment of the respective dates of commodity prices and Covid-19 case numbers. If the corresponding date fields are written in the same way, an inner join could help. In the present case, however, this would not be possible without prior adjustment, as the date notation of the tables differs considerably: 

Different date notation for commodity prices and Covid-19 case number
Figure 1: Different date notation for commodity prices and Covid-19 case number

The Intelligent Lookup function of the Data Warehouse Cloud provides a simple solution for this case. With the help of the "Fuzzy Match", users can independently define the score that is to be evaluated as a match. Instead of manually adjusting one of the two date fields, the matching values can be extracted directly. 

Result of the Intelligent Lookup: The data sources have 24 matching entries
Figure 2: Result of the Intelligent Lookup: The data sources have 24 matching entries.

In this example, 24 entries are marked as matches (see Figure 2). These are the 24 months between January 2020 and December 2021, as significant Covid-19 case numbers were only recorded in this period. This result can be used for visualisation in the SAP Analytics Cloud once it is stored as an Analytical Dataset in the SAP Data Warehouse Cloud. 

Data visualisation using the SAP Analytics Cloud  

In order to depict the multitude of different commodity prices with the worldwide Covid-19 case number on a monthly basis, a bar chart is suitable which accumulates the individual commodities. On this basis, user groups can decide independently whether they want to examine certain commodities in more detail within the given period. Particularly against the background of the much-noticed general price increase due to the Corona infection, this chart shows that a considerable number of commodities are not affected by it. Furthermore, a downstream increase in commodity prices can be observed, especially in the months following particularly high numbers of cases recorded worldwide. Further interpretations would require statistical analysis, but this graph nevertheless provides initial indications of a possible effect. 

Graph comparing Covid-19 cases (red) with commodity prices (bar charts).

Conclusion: How and where does the DWC Intelligent Lookup function help?

Thanks to the Intelligent Lookup function, the technical effort for data integration is kept within limits, making these work steps available to a broad group of users. In the existing example, this function was successfully applied using two data sources from the Data Marketplace. A similar approach can also be taken when combining an internal data model with an external data source. With the Intelligent Lookup function, the working environment of the SAP Data Warehouse Cloud becomes even more agile, which means that requirements for a data model can be designed even more individually. 

Learn more about Intelligent Lookup & DWC?

For more information on SAP DWC pricing, visit SAP's DWC pricing page or talk to us in person.

My team and I look forward to hearing from you.

Paul Vatter Head of the Data Warehousing Competence Centre at s-peers AG
Paul Vatter
Data workshop manager

Published by:

Lukas Weixler


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