A 2020 TDWI survey shows that the average data-driven organization will have more data on cloud than on premises by 2023. Many organizations have already passed this tipping point, and they will soon have only a small percentage of their data on premises.
Organizations are aggressively moving data and its management to the cloud for analytics as well as data science and machine learning because the cloud’s benefits apply directly to data management, namely elasticity for high-performance analytics processing and big data scale, but with minimal administration and entry costs for cloud platforms and tools. These benefits contribute to the success of business-driven programs in analytics, data science, reporting, warehousing, and time-sensitive operations.
However, achieving these business and technology goals depends on creating a practical, sustainable, and optimized architecture for cloud data and its applications across BI, data science, and machine learning. There are many layers in a modern cloud data architecture, but two layers stand out because they determine success or failure: the cloud data platform and cloud data integration. This webinar will drill into how these two layers work together to create a successful modern cloud data architecture.
By attending this webinar you will learn:
Individual, Student, & Team memberships available.