Modern BI and analytic al architecture has evolved beyond traditional DW with elements such as a l ogical data warehouse, data lakes, distribution hubs, data catalogs, analyt ical sandboxes, and data science hubs, along with both self-service data pr eparation and BI. But achieving a business return on investment (ROI) with these approaches is fruitless without the right data and technical architec tures. This workshop clarifies what you need to know regarding structured, unstructured, and semi-structured data; hybrid integration and data enginee ring; and analytical uses by casual info consumers, power users, and data s cientists.
\nThe technology categories with associated products to be discussed and positioned for use:
\n\n Databases (relational, columnar, in-memory, NoSQL, and Hadoop distributions )\n Data, application cloud, and hybrid data integration along with data prepar ation\n Data virtualization\n Descriptive, diagnostic, predictive, and prescriptive analytics\n Traditional BI and reporting versus data discovery tools\n On-premise, cloud, or hybrid deployments\n\nArchitectural concepts discu ssed:
\n\n Data structures and workflow\n Data engineering, data integration, data preparation, and data virtualizati on\n Business intelligence and advanced analytics\n Enabling technologies\n Enterprise information management and governance\n\n DTSTART:20181008T083000 SUMMARY:Designing a Data Architecture for Modern Business Intelligence and Analytics DTEND:20181008T114459 LOCATION: See Description END:VEVENT END:VCALENDAR