How Greene Tweed reduced time to insights by 65% for SAP data In this latest Data Science Central Webinar, enterprises are inundated with massive amounts of SAP data and challenged to create more consumable insights without increasing headcount or system resources. It is a daunting task to deal with slow systems and manual coding to gain any value from historical data spanning thousands of products, customers, sales history, and the list goes on. In this webinar, you'll hear how global manufacturer Greene Tweed developed an efficient, cost-effective, and logical strategy to connect Qlik Data integration and Microsoft Azure Synapse to build an intelligent supply chain for better business insight. Learn how Greene Tweed addressed their challenges and how they use data liberated from SAP for strategic analytics initiatives. In addition, you will discover: • How to create a plan of attack to extract insights from massive amounts of SAP data • How important change data capture is to building low latency extracts for massive data volumes • Why automation with Qlik Data Integration is crucial to expedite data availability • How SAP data drives insights to optimize Manufacturing & Supply Chain • The gains Greene Tweed realized by moving SAP data to Azure Synapse Register today to start your journey to improving data operations, accelerating reporting, reducing systems overhead and enabling AI operations with Qlik and Azure Synapse.

Azure Synapse Analytics is an unlimited information analysis service aimed at large companies that was presented as the evolution of Azure SQL Data Warehouse (SQL DW), bringing together business data storage and macro or Big Data analysis. Synapse provides a single service for all workloads when processing, managing and serving data for immediate business intelligence and data prediction needs. The latter is made possible by its integration with Power BI and Azure Machine Learning, due to Synapse's ability to integrate mathematical machine learning models using the ONNX format. It provides the freedom to handle and query huge amounts of information either on demand serverless (a type of deployment that automatically scales power on demand when large amounts of data are available) for data exploration and ad hoc analysis, or with provisioned resources, at scale. As one of the few Microsoft's Power BI partners in Spain, at Bismart we have a large experience working with both Power BI and Azure Synapse.

This week at Microsoft Ignite, a number of new developments to Azure were in focus. While there were dozens of updates to the world's second-largest public cloud, data was once again in the spotlight. The company made a series of announcements to enable users to extract more value from the exponential increase in data. Satya Nadella, in his Ignite keynote, provided a new visionary direction, or at least a new way of expressing the company's cloud endeavors. In short, the Microsoft cloud is evolving to further embrace edge, privacy, security, AI, and developers (both coders and no coders), and to serve as an engine of job creation. On the surface, this shift appears subtle.

We are really excited to introduce the preview of new machine learning experiences in Azure Synapse Analytics, to make it easier for data professionals to enrich data and build predictive analytics solutions. AI and machine learning is an important aspect of any analytics solution. By integrating Azure Synapse Analytics with Azure Machine Learning and Azure Cognitive Services, we are bringing together the best of two worlds, to empower data professionals with the power of predictive analytics and AI. Data engineers working in Azure Synapse can access models in Azure Machine Learning's central model registry, created by data scientists. Data engineers can also build models with ease in Azure Synapse, using the code-free automated ML powered by Azure Machine Learning and use these models to enrich data.