When you consider implementing artificial intelligence (AI), there is no such thing as too much data.
In fact, it is exactly the opposite. You need data, and lots of it, for AI to be effective. AI systems are designed to process massive volumes of data, which means that accuracy increases the more data is analyzed and the more data grows.
Consider retail merchandising and transportation systems. Customers rely on fully stocked shelves—both in-store and virtual—with a large variety of products that might originate from as close as next door or as far away as the other side of the planet.
SAP for AI Integration
According to Gartner, the global leader in supply chain software is SAP. This market has seen 13.9% growth in the last year. Cloud and AI are two reasons why. “Cloud solutions typically have lower barriers to entry and are more easily scalable, and are therefore a better fit for midsize organizations looking at SCM for competitive advantage,” said Balaji Abbabatulla, research director at Gartner. He also added that AI was another source of competitive advantage, because “AI can bring productivity and user experience improvements by automating routine tasks and providing more effective support to complex decisions.”
The integration of AI with merchandising and transportation systems enables the supply chains to more accurately support products being delivered at a higher velocity and with with greater reliability. Integrating AI into just-in-time SAP merchandising systems improves inventory turn while avoiding stock-outs, reduces spoilage, and gives better lead times for ordering products.
Looking for Patterns in SAP HANA
AI software embedded in SAP HANA looks for patterns in the data by using algorithms. For example, AI might sort through the data, looking at the days of the week alongside particular shipments of food to determine if spoilage rates are affected by shipping dates. AI might also determine if temperature has any effect on defects or which style of blue jeans is more likely to sell in the U.S. northwest versus Florida.
To effectively use AI, companies must provide as much data as possible and continue to add to that datastore. The addition of machine learning can increase the effectiveness of AI and increase opportunities to identify and then correct the actual cause of the problem.
According to ASUG (America’s SAP Users’ Group), SAP is leading in this effort by engineering AI within SAP HANA. SAP HANA clients are now getting started with AI by taking advantage of machine-learning capabilities—preconfigured decision-support scenarios that enable organizations to gain even greater insight from their data.
However, AI adds significant challenges to an already complex and highly integrated series of solutions:
The amount of data required by merchandising and transportation systems increases by an order of magnitude when AI is added to the picture, which can lead to increased delays in analysis and reporting.
SAP HANA data is often stored in disparate silos within the business and in external organizations, with a wide variety of technologies and data management systems.
Because customers expect shelves to be stocked constantly with their favorite products, the inventory status of individual items must always be known.
The volume of data changes regularly depending on season, special pricing,weather conditions, events, and several other variables.
On top of that, the velocity of data—the rate at which data changes—also increases dramatically.
Azure NetApp Files for SAP HANA on Azure
Azure NetApp® Files is the ultimate solution for supporting SAP HANA merchandising and transportation AI workloads. Azure NetApp Files supports massively large databases for Windows and open-source Linux environments, such as SQL and Oracle. With its low-latency and high-performance service levels, Azure NetApp Files can even support the extremely performance-intensive SAP HANA on Azure environment. Because all data is centralized in the cloud, cost and complexity are minimized.
Most important of all, the innovative design of Azure NetApp Files is ideally suited to the high velocity of constantly changing information required for an SAP HANA AI application.
Azure NetApp Files resolves many of the issues common to integrating AI with merchandising and transportation systems.
Azure NetApp Files supports high-velocity data analysis workloads required for AI solutions. Information changes quickly, and for AI to make the appropriate decisions, it needs to be able to get a real-time picture of any inventory at any time.
Scalability is a requirement of merchandising and transportation systems, which are always affected by seasonal and geographic concerns.