For most organizations today, the complexity a round data has increased rapidly. In the area of analytics, we have go ne way beyond the on-premises data warehouse and data marts of old and into big data Hadoop systems, NoSQL databases, streaming data platforms, c loud storage, cloud data warehouses, and IoT-generated data at the edge. In operational systems, we now have data in applications residing in data sto res on multiple different clouds as well in on-premises systems. Also, the number of data sources is exploding as companies ingest more and more external data such as weather and open government data. Some would say we a re awash with it. Silos have also appeared everywhere as business users are buying in self-service data preparation tools without consideration for ho w these tools integrate with what IT is using to integrate data. At th e same time, new regulations are demanding that we do a better job of gover ning data, and business executives are demanding more agility to remain com petitive in a digital economy where the customers can churn at the touch of a mobile phone screen.
\nSo how can companie s remain agile and reduce the time-to-value when data complexity is on an upward trajectory? In this keynote session, Mike Ferguson will loo k at this problem and discuss how companies can organize themselves and use artificially intelligent data management software to automate data discove ry, speed up data processing and use analytics to reduce time-to-value whil e regaining control of their data. The session will also show how a common approach to smart data management and analytics allows data and analytics t o become the foundation for the 'always on’ smart business.
\n DTSTART:20180424T084500 SUMMARY:Smart Data Management – Reducing Time to Value in an Increasingly C omplex Data Landscape DTEND:20180424T091459 LOCATION: See Description END:VEVENT END:VCALENDAR