Have you ever watched a robot vacuum cleaner at work? It starts off amusing, and slowly becomes progressively more irritating as you watch it miss the one patch of dirt you want it to clean. The promise of Artificial Intelligence is much the same –it can automate routine tasks and deliver significant tangible value; but if you aren’t careful, you might spend most of your time repeatedly bumping in to the same wall or getting stuck, tangled up in a mess of cables for the 20
th time. Unfortunately, there is some evidence that companies are spending more time tangled up than deriving value from AI:
- 84% of customers are concerned about the data being used to feed algorithms
- 86% of enterprises claim they are not getting the most out of their data
- 74% say their data landscape is so complex it limits agility
As with robot vacuums, the key to good results is to do a little tidying first. Artificial Intelligence makes use of complex mathematics and advanced computational power to deliver results but powering all of the fancy math and expensive hardware is data. Data is the lifeblood of artificial intelligence and without having a good grasp on the management of data, artificial intelligence will fail to yield positive results.
As companies moved from the traditional on-premise world where data was stored in governed databases underneath business applications like SAP ERP to one where applications are in the cloud and on-premise, with data coming from less structured sources (social media, weblogs, sensors), the landscape for data became more and more complex. This complexity came with a slew of new tools to try and manage all the new data types, formats, and locations. As companies tried to keep up with this flood of new data, the idea of the data lake as a single store of all data for later use became popular, giving rise to even more tools and techniques and soon there was a fracture between the highly governed data of enterprise IT systems, and the comprehensive but often ungoverned world of large scale data lakes and streams of data from weblogs, syslogs, sensors, IoT devices, and more. But Artificial Intelligence needs to connect to all of this data as well as image, video, audio, and text data sources. Simply trying to manage all of these connections has required multiple fractured and fragmented tools; until now.
SAP Data Intelligence, which was just announced at SAPPHIRE is a comprehensive cloud solution to scale Artificial Intelligence across the enterprise. It achieves this by managing three critical things:
- Manage the Data you need regardless of where it is or what kind of data it is
- Manage the Design of Machine Learning algorithms with the tools and frameworks your data science teams want to use
- Manage the Deployment of Machine Learning with cloud containers so IT can rapidly deploy, manage, and automate the end to end lifecycle of AI at scale
Artificial Intelligence is a team effort that requires coordination and cooperation between the business users that understand the needs of the organization and its customers, the data engineers that understand where the data is located and how it is structured, the data science teams that understand how to extract value from that data, and the IT and DevOps teams that support them. With SAP Data Intelligence every member of your AI team can work together for maximum productivity and speed. With built in tools for governance, metadata management, and machine learning transparency you can be sure that the results of their efforts can be explained, understood, and trusted.
Just as the second industrial revolution was driven by the assembly line for physical manufacturing, the fourth industrial revolution will be driven by the AI Assembly Line: the ability for the creation of AI to be broken down into specialized parts brought together by a business process and automated at scale. SAP Data Intelligence enables the creation of this AI Assembly line for organizations in a trusted and repeatable fashion so they can extract maximum value from their data assets and deliver the best experiences to their consumers and clients.
For more details on SAP Data Intelligence please visit
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