The Spark + AI summit Europe kicks-off in just a few days in London. Microsoft and many of their customers using Azure Databricks are present during the Summit. Azure Databricks is a first party service on Azure, allowing customers to accelerate big data analytics and artificial intelligence (AI) solutions with a fast, easy, and collaborative Apache SparkTM–based analytics service. Having such a platform improves developer productivity with a single, consistent set of APIs and developers can mix and match different kinds of processing within the same environment. Azure Databricks also improves performance by eliminating unnecessary movement of data across environments.
Here are a few recommended sessions you might find interesting, where customers and partners share success stories leveraging Azure Databricks:
For Oil & Gas
- Moving Towards AI: Learn from an actual customer how they are leveraging deep learning with Azure Databricks to implement a solution that enables them to detect safety incidents at their gas stations. Also learn how they were able to build an Advanced Analytics COE to lead AI projects across the organization.
- Co-op’s Transformation from Brick and Mortar to AI with Databricks: In this session, learn from the head of data within a consumer co-operative working in Food, Insurance, Funeralcare, among other markets how to lead data strategy, governance, and engineering while collaborating closely with teams across the company.
- Road to Enterprise Architecture for Big Data Applications: Mixing Apache Spark with Singletons, Wrapping, and Façade: Learn from a manufacture of high end automotive parts how they are incorporating big data and advanced analytics worldwide. In the Manufacturing industry, reliability and time to market are key factors to accomplish business goals. Nowadays, analytics are more and more deployed to get insights’ from data and foster a data driven culture to achieve a greater effectiveness and efficiency within business operations. In the analytics domain, real challenges are often represented by data collection, such as the existence of heterogeneous and widespread data sources, the choice of ingestion technologies and strategies, the need to ensure a continuous data inflow, and release production-ready analytics services to be integrated into in daily operations. Learn how the customer is over coming these challenges to adopt AI.
- Using Apache Spark Structured Streaming on Azure Databricks for Predictive Maintenance of Coordinate Measuring Machines: Learn from a data scientist how he and his team build digital products for their organization. The session will talk about how they use Apache Spark Structured Streaming on the Azure Databricks, to process live data and Spark MLlib to train models for predicting machine failure. This allows users to stay on top of all relevant machine information and to know at a glance if a machine is capable of performing reliably. He will demonstrate how Azure Databricks allows the team to easily schedule and monitor an increasing number of Spark jobs, continuously adding new features to the app.
- Azure Databricks, Structured Streaming, and Deep Learning Pipelines to Monitor 1,000+ Solar Farms in Real Time: Also in manufacturing, learn from this technical deep dive session about the fundamental architecture, technology, and approach that makes the platform work, beginning with key features of the Azure Databricks cloud and how it works seamlessly with Azure Data Lake and Azure Event Hubs. There will be good coverage of ML and DL Pipelines and how they are used with image recognition and machine learning through Structured Streaming to make real-time decisions, such as:
- Near-real time processing of image data at frequent intervals to predict cloud cover from onsite cameras
- Drone Analysis of data and preventative maintenance of fan failures in solar inverters
For Public Sector
- Fireside Chat: Join this fireside chat to learn from a long time business leader in business intelligence, data and transformation, both here in the UK operating company and abroad. Learn how to define BI and big data strategy and lead on the execution of a major transformation programme to deliver it. Also learn how to be the champion of data at board level, making sure data is treated as the incredible strategic asset that it is.
For Lambda Architecture in the cloud
- Lambda Architecture in the cloud with Azure Databricks: Another session with a real customer scenario. In this talk the customer demonstrates the blueprint for such an implementation in Microsoft Azure, with Azure Databricks as a key component. You will learn some of the core principles of functional programming link them to the capabilities of Apache Spark for various end-to-end big data analytics scenarios. You will also see “Lambda architecture in use” and the associated trade-offs using a real customer scenario – a terabyte-scale Azure-based data platform that handles data from 2.5M visitors per year.
Source: Azure Blog Feed