Build a Business Transformation Vision with Google Cloud

Each participant will leave with a recognised certificate

Module 1: Then and Now

• Objective: Differentiate ​Google ​Cloud ​from ​traditional ​technology through ​financial ​and ​IT ​lenses.

• Topics ​covered:

• What ​is ​a ​traditional ​business ​IT ​anatomy?

• How ​have ​business ​needs ​prompted ​the ​evolution ​of ​IT over ​the ​years?

• What ​is ​Cloud? ​What ​is ​unique ​about ​Google ​Cloud?

• How ​does ​Google ​Cloud's ​technology ​and ​cost ​model address ​business ​challenges?

Module 2: Creating Value

• Objective: Describe ​the ​top ​ways ​Google ​Cloud ​Platform ​(GCP) innovatively ​reduces ​costs ​and ​creates ​values.

• What ​are ​the ​GCP ​product ​categories ​and ​what ​business ​needs do ​they ​address?

• How ​does ​GCP ​innovatively ​reduce ​costs?

• How ​does ​GCP ​innovatively ​create ​value?

• What ​are ​some ​business ​transformation ​cases ​that ​use ​GCP?

Module 3: Culture of Innovation

• Objective: Explain ​the ​process ​to ​promote ​a ​culture ​of ​innovation ​using examples.

• What ​are ​the ​pros ​and ​cons ​of ​innovation ​and ​disruptive innovation?

• What ​are ​the ​steps ​to ​promote ​a ​culture ​of ​innovation?

• What ​enables ​and ​inhibits ​innovation? ​What ​are ​some ​examples?

• How ​can ​I ​promote ​a ​culture ​of ​innovation ​today?

Module 4: Secure and Compliant

• Objective: Describe ​Google's ​multi-layer ​measures ​to ​ensure ​customer data ​is ​secure, ​private, ​and ​compliant ​per ​government ​or ​industry regulations.

• What ​are ​today's ​top ​data ​and ​security ​threats/challenges?

• How ​are ​compliance ​requirements ​shifting ​with ​Cloud ​technology?

• What ​are ​top ​Google ​Cloud ​Platform ​(GCP) ​measures ​to ​maintain data ​and ​network ​security?

• How ​can ​you ​manage ​governance ​(GRC) ​with ​GCP?

• Workshop: Transformation Vision

• Objectives: Build ​a ​business ​transformation ​vision ​using ​Google ​Cloud ​product capabilities.

• Round ​1: ​Identify ​business ​challenge

• Round ​2: ​Explore ​machine ​learning ​use ​cases

• Round ​3: ​Brainstorm ​potential ​solutions ​using ​data

• Round ​4: ​Prioritize ​potential ​solutions