by twieberneit | Jan 12, 2017 | Analysis, Blog |
On January 10, 2017, SAP announced a bundling of their IoT portfolio of initiatives to focus on business outcomes instead of technology while combining the set of emerging products and solutions under the brand name Leonardo – as in Leonardo Da Vinci, one of the most forward looking artists and innovators ever. This announcement substantiates SAPs commitment to invest two billion Euro in IoT over the next 5 years. The new portfolio will combine adaptive applications, big data and connectivity as packaged line-of-business solutions, covering a range of topics. It bases upon a rebranded – and repackaged(?) HANA Cloud Platform, enhanced by the micro services for machine learning that were announced earlier and which I covered here. This enhanced platform is now called SAP Cloud Platform. As per a blog post accompanying the Leonardo announcement, the high level architecture of SAPs new offering looks like below and covers, besides a set of existing applications an IoT adapter – SAP Leonardo for Edge Computing – which serves as a device independent data input layer, essentially a kind of middleware, probably built on or using HCI. a foundational layer – SAP Leonardo Foundation – which includes the IoT business services that are to be exposed, enabling rapid development of applications. This makes up the functional core. and a ‘bus’ layer – SAP Leonardo Bridge – which enables the combination of real time data with applications and processes Leonardo is accompanied by a jump-start enablement program to accompany this initiative. This program includes introductory pricing and is intended to help organizations identify and validate IoT pilots and use cases, including expert staffing...
by twieberneit | Nov 10, 2016 | Analysis, Blog |
In my yesterday’s analysis of SAP’s HANA announcement, I wondered why SAP stays silent on the AI and MachineLearning frontiers. Well, today I know. They saved this announcement for today. And the announcement is a bang. SAP will deliver what they call ‘intelligent business applications’ that are based upon SAP’s new machine learning platform. The platform itself shall be made available with SAPPHIRE NOW 2017. The first significant intelligent application by SAP that is mentioned, is a brand intelligence application that leverages deep learning to analyze brand exposure in video and images to provide ‘accurate, real-time insights into sponsoring and advertising ROI”. You may remember that SAP earlier showcased an application to reduce recruiting bias, which is based on the machine learning platform, too. According to Juergen Mueller, Chief Innovation Officer at SAP, the new machine learning platform is intended to serve SAP’s and their ecosystem’s applications with the goal of creating more business value. Consequently, there are two more aspects to the announcement. SAP launched a partner program dedicated to SAP Application Intelligence. SAP invests into education offerings, starting with a ‘massive open online course’ on Enterprise Machine Learning on their OpenSAP platform. MyPoV This announcement clearly shows that SAP is as serious about machine learning as the company is about leveraging the power of its ecosystem. As I, and many other people, have often said, SAP is a formidable organization if and when it chooses to drive a topic. This is shown here again. And SAP is absolutely on the right track by pursuing this three-pronged approach of delivering a platform with first solutions, encouraging partners, and...
by twieberneit | Oct 11, 2016 | Analysis, Blog |
Following all those announcements of AI, machine learning, IoT, IaaS, PaaS and what not over the past months, I was beginning to wonder where the big business software vendors are going. What is the game plan of Microsoft, Oracle, Salesforce, SAP? How does newcomer Adobe fit in there? Maybe Amazon and Google, too; or Facebook. It is a time for another Quo Vadis – this time: Quo Vadis, industry? Clash of Titans In the last about 2 – 3 years we have seen a strong acceleration of innovation, or at least talk about it. Cloud computing, offering nearly unlimited scalability and elasticity of computing resources has become main stream. Cloud computing also allows for nearly 100 per cent uptime Since the advent of the iPhone (yes, I know this was earlier than 2013) the proliferation of sensors has increased a lot, resulting in them becoming cheaper and cheaper, allowing for an increasing number of data rich applications This has also driven fast mobile connectivity, which has become nearly ubiquitous; maybe except a few blessed spots on this planet, which will be covered soon, too. Think of Google’s Balloon project or Facebook’s drone Memory has become dirt cheap, and fast In-memory technologies, No-SQL databases, Hadoop, Spark, and improvements of analytics algorithms make it possible to work with huge sets of data in real time The (re-)emergence of AI technologies, progress in machine learning and deep learning, enabled by the now available computing power, help in pattern recognition that allows machine driven suggestion, prediction, and prescription of actions, based upon huge amounts of data Data, be it machine-generated or human created...
