ANALYTICS

Set up data in SAP Analytics Cloud


One of the things that sets SAP Analytics Cloud apart is the fact that you can model your data right inside the app.

data preparation
Data preparation is also known as data wrangling and is the first stage of modeling. It’s when you clean and transform your data in preparation for analysis.
Forms can be created from files imported from your computer, Google Drive, or from connected workplace data and cloud data sources through data import connections. please note: Data preparation and modeling within Analytics Cloud is not possible, or not necessary for data sources connected via live data connections. This is because live data communications use existing models with your source systems and are updated with new data in real time.
In this blog post, I will walk you through the process of preparing your data with Analytics Cloud Modeler.

I will show you:

  • How to check a file data quality?
  • How do you define relationships within your data?
  • How do you update your data quickly with quick actions and conversion?
  • how to arise Geolocation?

OK!! let’s start with data modeling.

  1. In the SAP Analytics Cloud window, expand File Navigation Bar > More > Choose Template Designer. Before that, just try to understand what set of data you are going to use.

2. Since our data set is an Excel spreadsheet, we will choose a format “Import a file from your computer” Selection.

Choose %20 from %20a %20CSV %20 or %20Excel %20 File

Choose from CSV or Excel file

3. Upload the Excel file you have already downloaded.

4. Make sure the first sheet labeled . is selected “download data” and click “Import”.

Choose %20Data%20Upload

Choose Load Data

5. If the imported file consists of a large number of records, you will see that the data has been sampled. Data sampling helps Analytics Cloud run faster while preparing data. Changes you make to this sample will be applied to the entire data set once your model is created.

Data %20 Sampling %20 Done %20 Done

The data was sampled

6. Once you have finished sampling the data, give OK. Then you will see a file data integration Workspace subordinate designer.

Data %20 Integration %20 Workspace %20 of %20 Form %20

Form data integration workspace

7. You will notice that there is no option to save in the toolbar. This is because the process of preparing your data should be done in one session.

8. Once the data has been imported, you will see it organized in a familiar row and column format. This is called table view.

9. Data summary and form information: to me Your data right, the detail panel displays a data summary And Form information. You can use the panel to update model information and choose from some model options. Since this form is for analysis only, we will leave a file “Planning is possible” The option is not specified.

10. To get a good overview of your data set, you can switch to Card display form (You can find the card view template in the top navigation bar of the Layout section).

Card %20

card view

card view: Each card represents a column of data and shows some summary information. When you select a card, detailed information about the column appears in the detail panel.

11. Let’s start by checking how columns are categorized:

11.1 Are the scales and dimensions defined correctly? Yes… It is very important to check if the metrics and dimensions are defined correctly or else you will have problems in future calculations. For a better understanding, let’s see what are the scales and dimensions…

procedures: The scale contains quantitative information that can be used for calculations.

DimensionsDimensions are qualitative and help provide context.

misclassification is unlikely to happen. Because Analytics Cloud recognizes data patterns and is usually able to infer whether or not a column of numeric values ​​is a measure or a dimension. So always checking it once would be fine.

For %20 Example %20 in %20this%20 Image %20 Information %20 in %20%20count%20 Column %20 represents %20 Issue %20 of %20 Travelers %20 in %20each %20record %20 This %20 %20 means that %20%20 Column%20is%20a%20 Scale%20 No%20a%20 Dimension%20so%20lets%20 Refresh%20%20 Datatype%20in%20 Top%20 Image

For example, in the top image information in the Count column represents the number of travelers in each record and that means the column is a scale and not a dimension, so let’s update the data type in the top image.

11.2 The Details panel is also where you can add dimensions such as descriptions, properties, and hierarchies to your existing dimensions. Well.. let’s discuss it now:

Describe: The descriptions provide context for the dimension columns that are identifiers.

Properties: Properties consist of dimensional information.

Hierarchies: Hierarchies are dimension attributes that create a parent-child relationship. These relationships will allow you to search for different levels of detail in your diagrams.

Noticeable: You can also add data descriptions to your dimensions later (I mean once after the model is created). But if you ever will, please sort the cards from A to Z so it’s easy. Then keep something in mind that the number of unique values ​​in the identifier must match the values ​​in the description card.

11.3 Geolocation– The latitude and longitude coordinates in your dataset will be used to generate geographic locations.

11.4 Another part of preparing the data is cleaning your data and making sure that only relevant data is included in the form which is an important part too🧐.

11.5 choose a measures card It allows you to check data quality and see data distribution in detail panels. At this point, make sure that all data makes sense. for example: If you are going to include values ​​greater than $0, you can remove this record from your form.

11.6 After all these things pop up again and check if all the columns of the data set are necessary for the analysis. If any columns do not contain any values, just delete them using quick actions.

11.7 data conversion: While it comes to converting your data, you can choose from the smart conversion suggested by Analytics Cloud or create your own conversion using the conversion bar.

11.8 Now all things are ready for your data modeling. Yes!!! You people are very excited, aren’t you? Now just give Create a form Available at the bottom right in the detail panels.

11.9 Okay! Now your form has been created just save them. Your form is now completely ready for analysis purposes.

I think so, the above steps will be helpful in preparing the data. Then please remember to always double check the metrics and dimensions or else you will have problems with the calculation part while building your story. And also save some time on the description, characteristics, and hierarchies of effective data modeling.

If you have questions regarding the content you just read, feel free to post your questions in the dedicated SAP Analytics Cloud tag: https://answers.sap.com/questions/ask.html?

Please also follow the tag: https://answers.sap.com/tags/67838200100080006884 and make sure you enable your communication settings (https://people.sap.com/#communities) to stay up to date with content in SAP Cloud Analytics.

Check out the SAP Analytics Cloud topic page as well: https://community.sap.com/topics/cloud-analytics. Give your feedback in the comments section, and I look forward to reading it!

Well let’s meet you guys on another blog. Thanks for reading… Bye!!



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