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The new version of the SAP S/4HANA Cloud SDK Java libraries is available since today. You can update your dependencies to version 1.8.0 and consume the new version from Maven Central.
In this blog post, we will walk you through the highlights of these releases. For a complete overview, visit our release notes for the Java libraries. The release notes also include the change log of all our releases so far.
At the end of the article, you will find a set of instructions on how to update to the new version.

Java Libraries: Release Highlights

Note: If you are using the SAP S/4HANA Cloud SDK in the Neo environment of SAP Cloud Platform, please note that there is a bug in the SDK that affects multi-tenant applications on Neo. We recommend NOT to update to version 1.8.0 in case of a multi-tenant application on Neo. Instead, wait for the next release of the SAP S/4HANA Cloud SDK, in which we plan to fix this bug. You can safely proceed to update the SDK version in Cloud Foundry applications.
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As part of the SAP S/4HANA Cloud SDK, we also provide integration to popular third party frameworks on SAP Cloud Platform, for example Togglz or EclipseLink. Another example is Apache CXF; an open-source framework for developing services. With this version, we have extracted the JAX-RS specific functionality of the Apache CXF integration module into a seperate module com.sap.cloud.s4hana.frameworks:jaxrs to make it easier to leverage the corresponding functionality such as JSON message (de)serialization and error handling in applications that do not use Apache CXF.

The Javadoc of the SAP Cloud Platform abstractions (classes in packages com.sap.cloud.sdk.cloudplatform.*) has been improved to make it easier to use the corresponding functionality of the SAP S/4HANA Cloud SDK, which provides simple and transparent access to Cloud Platform features such as connectivity, security, tenants or audit logging, on both Cloud Foundry and Neo.

We have improved the contracts of methods for handling tenant, user and secret store by introducing more specific exceptions.

We have also changed names and packages of several classes – please take a close look at the compatibility notes for the full list of changes.

On some developer machines, deploying the app on the local TomEE server based on the scp-cf-tomee archetype may have failed previously with exceptions such as java.lang.NoSuchMethodError: org.apache.tomcat.util.ExceptionUtils.preload()V. We have resolved this issue by removing the tomcat-catalina lib from the TomEE Maven plugin configuration in the application/pom.xml file as generated by scp-cf-tomee archetype. Newly generated project will no longer produce this error. If you have previously generated a project using that archetype and experience the same issue, manually remove the following lines at the end of application/pom.xml: org.apache.tomcat:tomcat-catalina:7.0.82

We have also fixed several further issues as explained in the full release notes.

How to Update: Java Libraries

Note: As mentioned above, we recommend NOT to update the SDK for a multi-tenant application on Neo.

To update the version of the SAP S/4HANA Cloud SDK Java libraries used in an existing project on Cloud Foundry, proceed as follows:

* Open the pom.xml file in the root folder of your project.
* Locate the dependency management section and therein the sdk-bom dependency.
* Update the version of that dependency to 1.8.0.

With this, you are already done thanks to the “bill of material” (BOM) approach. Your dependency should look like this: com.sap.cloud.s4hana sdk-bom 1.8.0 pom import

You can now recompile your project (be aware of the compatibility notes, though) and leverage the new features of the SAP S/4HANA Cloud SDK in version 1.8.0.

Of course, you can also generate a new project that uses version 1.8.0 from the start by running the Maven archetypes for Cloud Foundry with -DarchetypeVersion=1.8.0 (or RELEASE). http://bit.ly/2C5oqDG #SAP #SAPCloud #AI

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New trends in predictive analytics, artificial intelligence, and machine learning are calling into question many traditional processes — and that includes the provision of business intelligence inside organizations.

Please join me and SAP Analytics Evangelist Andy Bitterer to discuss the trends, the biggest challenges, and potential use cases of these technologies on February 7, 2018, at 8am Pacific Time (5pm CET) as part of an #askSAP Live Chat on Facebook. Please bring your questions!

Here are just some of the areas we’ll be exploring:

* Why, after being the “next big thing” in analytics for at least two decades, Predictive Analytics and Machine Learning are now such hot industry trends.
* How machine learning is enabling “self-driving” processes that automate the kinds of complex repetitive decision-making that up until now only humans could do.
* The biggest new opportunities for these technologies in today’s organizations.
* How companies can get started with machine learning.

In particular, we’ll be talking about what machine learning can bring to traditional analytics, including:

* More intelligent data preparation. Over 90% of average business intelligence projects involve gathering, cleaning, and joining data from different sources. Algorithms can help automate some of this work, especially for more casual business users.

* Natural-language interfaces. BI interfaces that correctly interpret user questions in everyday language via voice or chat, such as “what’s the revenue per customer this month compared to last month?” and are able to provide data in sentence form, such as “deal value is 20% lower than average for the enterprise segment”.

* Automatic outlier detection. Algorithms can spot exceptions and unusual events automatically, such as: “days sales outstanding is the western region is currently 90% higher than the average over the last six months”. This helps enable the long-term dream of true exception-driven management.

* Intelligent segmentation. Statistical techniques can automatically create groups and segments that make sense based on the data, rather than arbitrarily-defined thresholds. For example, by automatically segmenting crime data into age-ranges that match real-world trends, such as 0-14, 14-23, 23-35 etc. rather than 0-10, 20-30, etc.

* Causality and significance detection. We can use algorithms to determine the key influencers on profitability, or to check whether an uptick in sales is a real inflection point rather than just random variation.

* Advanced data sharing. Just as Amazon recommends book purchases based on what we’ve read in the past, algorithms can help identify reports and data that we might be interested in — “people like you also liked this dashboard”.

The more interactive the session, the better. We look forward to hearing and answering your real questions (rather than having to guess what you might be interested in!) — and please tell us if you can make it by clicking “going” or “interested” on this page! http://bit.ly/2EAacfI #SAP #SAPCloud #AI