Ariba Analytics using SAP Analytics Cloud, Data Intelligence Cloud and HANA DocStore – Part 1

Introduction

SAP Analytics Cloud makes it easy for businesses to understand their data through its stories, dashboards and analytical applications. However, sometimes we might not be sure how we can leverage SAC to create these based on data from other applications

For this worked example, we’re going to make use of SAP Data Intelligence Cloud to retrieve data from SAP Ariba through its APIs, before storing it in SAP HANA Cloud’s JSON Document Store

In further blog posts, we will build a model on top of this stored data and show how this can be consumed in an SAP Analytics Cloud Story. The focus of this series of blog posts is to show a technical approach to this need, not to provide a turnkey ready-to-run SAC story. After following this series you should have an understanding of how you can prepare your own stories using this approach

Ariba Analytics in SAP Analytics Cloud

For this example, we’re going to create a simple story that lets you know how much spend has been approved within Ariba Requisitions created in the last thirty days

A Requisition is the approvable document created when a request is made to purchase goods or services. Our approach will let us view only the Approved Requisitions, excluding those still awaiting approval

For those feeling more adventurous, this setup can be repeated with different document types, and those combined to create more in depth SAP Analytics Cloud Stories. This is outside of the scope of our blog series

Solution Overview

Our finished solution will need SAP HANA runtime artifacts such as Document Store Collections, SQL Views and Calculation Views. We will define these as design-time artifacts in Business Application Studio, then deploy them to an HDI Container within our SAP HANA Cloud instance

Using a scheduled SAP Data Intelligence Cloud Pipeline, we’ll query SAP Ariba’s APIs and place the data within our HANA Cloud Document Store Collection

Our SQL View lets us create a view on top of the data within our JSON Documents. Creating a Calculation View on top of one or many SQL views will let us expose the data to SAP Analytics Cloud

SAP Analytics Cloud can use HANA Cloud Calculation Views as the source for Live Data Models. With Live Data Models, data is stored in HANA Cloud and isn’t copied to SAP Analytics Cloud

This gives us two main benefits: We avoid unnecessarily duplicating the data, and ensure changes in the source data are available immediately (provided no structural changes are made)

Finally, we use the Live Data Model to create a Story within SAP Analytics Cloud. Once we’ve got everything set up, we can use this story to check our data at any time, with the Data Intelligence Pipeline refreshing the data in the background on a predefined schedule

Creating an Ariba Application

In order to access the APIs provided by Ariba, we’ll need to have what’s known as an Ariba Application. We do this through the SAP Ariba Developer Portal

For our use case we will be requesting access to the Operational Reporting for Procurement API

Once the Application has been created, we’ll need to request API access for the Application

Once the API Access Request has been approved by Ariba, your admin will be able to generate the OAuth Secret for our application

This will generate our OAuth Secret, which is required to use the API. The secret will only be displayed once, so the admin should (securely) store this and provide it to you for use in the application

If the OAuth Secret is lost, the admin can regenerate it, at which point the old secret will stop working and you will have to use the newly generated secret

Ariba API

When we call the Ariba API, we have a number of things to consider. For our example, we’re using the Synchronous API to retrieve data, but there’s also a set of Asynchronous APIs you should consider when retrieving bulk data

In addition, when retrieving data sets, you have to specify an Ariba View that you wish to retrieve. These are similar to reporting facts in the Ariba solution, such as Requisition or Invoice. Views will specify which fields are returned, and may also specify filters you should provide when calling them

To simplify our example we’re going to use a System View, which is predefined in Ariba. You are also able to work with Custom Views using the View Management API to better match your requirements but this falls outside the scope of this blog series

To explore these at your own pace, you can visit developer.ariba.com

Enabling Document Store in HANA Cloud

The Document Store is SAP HANA Cloud‘s solution for storing JSON Documents. While the Column and Row Stores use Tables to store their data, the Document Store stores data inside Collections

Before we activate the Document Store in HANA Cloud, just a word about resources. Like the Script Server, the Document Store is an additional feature that can be enabled, however we should consider HANA Cloud’s current resourcing before enabling it.

When we’re ready to enable, we’ll need to navigate to SAP HANA Cloud Central.

From HANA Cloud Central, we can then activate the Document Store

Once our HANA Cloud instance has restarted, we’ll be able to use the Document Store

Creating a DocStore Collection in Business Application Studio

While we can create a Collection directly using SQL through Database Explorer, we want to make sure we also have a design-time artifact for our DocStore Collection

To do this, we’ll use the Business Application Studio. For those unfamiliar with Business Application Studio, you can follow this Learning Journey Lesson to set up a Workspace – we’ll assume this is already in place

It’s time to set up our SAP HANA Database Project, and create the HDI Container where our runtime objects will reside

Next we’ll need to provide some information for our project

Double check the Database Version and Binding settings then click Next

Next we have to bind the project to a HANA Cloud instance within Cloud Foundry. The Endpoint should be automatically filled, but we have to provide our Email and Password before we can perform the binding

For this example we’re going to create a new HDI Container

If our Cloud Foundry space has more than one HANA Cloud instance, we may want to disable the default selection and manually choose the HANA Cloud instance where our container will reside

Now that we have our HDI Container and SAP HANA Project set up, it’s time to create our design-time objects. First, we login to Cloud Foundry

Next, we’ll create our DocStore Collection

After the deployment is successful, we have both our design-time .hdbcollection artifact, as well as the runtime DocStore collection which has been created in our HDI Container

Creating our Connections in Data Intelligence

So far we’ve gained access to Ariba APIs and enabled the Document Store in our HANA Cloud Instance. Next, we’ll be setting up two Connections in Data Intelligence Cloud

The first Connection will allow our Data Intelligence Pipeline to query the Ariba APIs to retrieve our data, and the second will allow us to store this data in the Document Store within our HDI Container

First, we use the DI Connection Manager to create a new Connection, selecting OPENAPI as the Connection Type

Our OpenAPI Connection will be used to send the request to Ariba. We’re going to set the connection up as below, using the credentials we received when we created our Ariba Application

Next, we’re going to create a HANA Connection that will let us work with the HDI Container we created earlier. To get the credentials, we have to go to the BTP Cockpit

We’ll want to keep this window open as we create our HANA DB Connection, as it has the details we need. Within Data Intelligence Cloud, create a new connection of type HANA_DB and fill it out as below using the credentials

While we have the credentials open, take note of the Schema name. We’ll need this to set up our pipeline

Pipeline Overview

The source code for our pipeline can be found. Copy the contents of this JSON to a new Graph within the Data Intelligence Modeler. If you’re not familiar with how to do this, you can refer to the README

When the pipeline starts, a GET request is made to the Ariba API. If there are more records to be fetched, the pipeline will make further requests until it has all available data. To avoid breaching Ariba’s rate limiting, there is a delay of 20 seconds between each call

Once all of the records have been fetched, the Document Store Collection is truncated to remove outdated results, and the most up to date data is inserted into our collection

1. A copy of the data is stored as a flat file in the DI Data Lake as reference
   
2. The HANA Document Store Collection is truncated, and Documents are added to the Collection one at a time
   
3. Once all records have been added to the Collection, the Graph will be terminated after a configurable buffer time (1 minute by default)

Configuring our Pipeline

In order to run this pipeline, you will have to make some changes to the pipeline:

In the Format API Request Javascript Operator, you should set your own values for openapi.header_params.apiKey and openapi.query_params.realm

If your Connection names are different to ARIBA_PROCUREMENT and ARIBA_HDI, then you will want to select those under Connection for the OpenAPI Client and SAP HANA Client respectively

Check the Path values for the operators “Write Payload Flat File” and “Write Error Log”. This will be where the pipeline will write the Flat File and API Error Logs respectively. If you’d like them to save elsewhere, edit that here

Finally, we’ll want to set the Document Collection Schema name in the DocStoreComposer Operator. This is the Schema we noted earlier while setting up the Connections

Testing our Pipeline

Now we’re ready to test our pipeline. Click on Save, then Run

Once our pipeline has completed successfully, we’ll be able to see that our JSON Documents are stored within our Collection by checking in the Database Explorer. We can access this easily through Business Application Studio by clicking the icon next to our SAP HANA Project

We can see that our pipeline has been successful, and that 206 JSON Documents have been stored in our Collection

Wrap-Up

In this blog post we’ve walked through how we can use SAP Data Intelligence Cloud to extract data from SAP Ariba, before storing it in a collection in SAP HANA Cloud’s Document Store