“William McKnight is an Analyst for Gigaom Research who takes corporate information and turns it into a bottom-line producing asset. He’s worked with companies like Dong Energy, France Telecomm, Pfizer, Samba Bank, ScotiaBank, Teva Pharmaceuticals and Verizon — 17 of the Global 2000 — and many others. William focuses on delivering business value and solving business problems utilizing proven, streamlined approaches in information management.”
This free one-hour webinar will present the findings of a recently completed Sector Roadmap for Cloud Analytic Databases.
The cloud is proving immensely useful to providing elastic, measurable, on-demand, self-service resources to organizations. The uptake in 2016 has been phenomenal, continuing the biggest transformation that technology professionals will experience in their careers.
Just about any software, including databases, can be placed in a public cloud these days by simply utilizing cloud resources as an extended data center. This may solve an immediate pressing problem, but the opportunities missed without true cloud integration are huge.
Some relational databases have undergone significant cloud-related development in their latest releases. Those were the focus of this Sector Roadmap, along with the databases built native for the cloud.
The methodology will be reviewed, along with the disruption vectors (criteria prominent in a cloud analytic database selection), and the key takeaways, all with a view to help the attendee select their cloud analytic database in 2017.
Join Gigaom Research and our sponsor Snowflake Computing for “Sector Roadmap for Cloud Analytic Databases: Selecting a Data Platform in 2017”, a free expert webinar on March 9.
What Will Be Discussed:
– Data architecture for 2017
– Data platform selection in 2017
– Major criteria often overlooked in database selection
– Why a tight integration with the cloud is imperative (“born in the cloud”)
– Other key takeaways from the study
Who Should Attend:
– Enterprise developers
– CIOs, purchasers and recommenders of data platforms
– Business users
– Database, BI and Big Data architects
– Developer managers
– IT decision makers