Service Now connectivity using SOAP query through HANA SDA

Overview

In this article, the method of connecting Service Now with HANA SDA connection is explained along with the set up for the delta connection is described. The scenario described here will explain the connectivity with Service Now and the data extraction techniques.

Connectivity with Service Now

Connectivity with Service Now from HANA is possible through SOAP adapter. Once the adapter is set up, a connection needs to be created in HANA IDE. This is possible through the SDA option. Please note that the data is always accessed virtually and there is no need of replicating the data for the connection.

Mapping Risk in a Stormwater Network using SAP HANA Spatial and Graph

In this blog post I will show how to estimate the water load in a stormwater network and calculate the risk of an overload. Sure, I’m not a water network expert, but here is the idea: a stormwater network is a directed, (in our case mostly acyclic) graph made up of a set of edges/pipes and vertices/junctions. For each vertex we can calculate the catchment area, i.e. the area from which rain water most likely will enter the network via that vertex. Each vertex then propagates the load to its downstream network. By looking at the ratio of the pipe’s load and cross-section, we can estimate the overload risk for each pipe.

Monitoring & Analysis for SAP HANA Platform

The described aims to enlighten the audience about the Real-time Monitoring capabilities exposed by the SAP HANA platform. System Administrators maintain the integrity and consistency of the SAP HANA platform by performing regular system monitoring which helps with identifying system behavioral patterns. A combination of monitoring tools and checks provides a detailed technical overall system health check and helps with identifying and forecast requirements against possible data & Hardware bottlenecks.

An adequate System monitoring exercise involves continuous monitoring of the following but not limited to these environmental components:

Augment your Python Analysis with Multi-Model data in SAP HANA Cloud

A lot of data science and machine learning work is done in Python. For this, the “Python machine learning client for SAP HANA” (hana-ml for short) provides easy access to SAP HANA tables in the form of Pandas compatible data-frames. However, with its multi-model capabilities (like spatial, graph, and document store), SAP HANA has more to offer. In this blog post, you will learn about the enhancements of the library to support these multi-model capabilities and how you can leverage them for your work. We will walk through an end-to-end example based on Wellington’s stormwater network. We will evaluate and visualize the graph and show how we can analyze problems that might occur in the network based on built in graph algorithms. The data and code is available on github.com. If you want to run the Jupyter Notebook yourself, you need to take care about the prerequisites.

Know Your Dependencies – Network Tracing with SAP HANA Graph

In this blog post, I will show how to use some basic SAP HANA Graph functions to understand dependencies in a directed graph. The demo data describes python packages and their dependencies. Resolving package dependencies is required if a package manager like “Anaconda” needs to check for pre-requisites before installing a new package. However, the patterns discussed in this article are generic and apply to use cases in manufacturing, utilities, IT and many other industries. The data and code is available on github.

Using the graph engine in SAP HANA for Master Data Substitution

What is Master Data Substitution?

Master Data Substitution is a process when requested master data entity can be substituted by another one. Master Data substitution is very generic framework which supports different master data entities and provides various features like Exclusion, Grouping, Context Objects, Validities etc.

Example: Product Substitution. In Sales order, if Customer is requesting for Product A, but this product A is not available due to out of stock or for any other reason we will not be fulfilling customer demands. But Product B is available which is having the similar specifications as product A, then Product B can be substituted and fulfill customer demands. Product B can further be substituted with Product C and Product C can be substituted with Product D.