Suppliers United States Google Cloud Platform
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Google Cloud Platform

United States
Mountain View
2008
Private
$1-10b
10,001 - 50,000
Open website

Google Cloud Platform, offered by Google, is a suite of Cloud Computing services that provides a series of modular cloud services including computing, data storage, data analytics, and Machine Learning, alongside a set of management tools.

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Google Cloud Platform is a provider of Industrial IoT infrastructure as a service (iaas), analytics and modeling, platform as a service (paas), networks and connectivity, robots, sensors, functional applications, cybersecurity and privacy, application infrastructure and middleware, and automation and control technologies, and also active in the agriculture, apparel, automotive, buildings, cement, construction and infrastructure, consumer goods, e-commerce, education, electrical grids, equipment and machinery, finance and insurance, food and beverage, glass, healthcare and hospitals, life sciences, national security and defense, packaging, plastics, retail, telecommunications, and transportation industries.
Technologies
Analytics & Modeling
Big Data Analytics
Computer Vision Software
Digital Twin / Simulation
Machine Learning
Predictive Analytics
Real Time Analytics
Infrastructure as a Service (IaaS)
Cloud Computing
Cloud Databases
Cloud Storage Services
Private Cloud
Public Cloud
Virtual Private Cloud
Sensors
Barcode Readers
Camera / Video Systems
GPS
Level Sensors
Temperature Sensors
Functional Applications
Enterprise Resource Planning Systems (ERP)
Fleet Management Systems (FMS)
Manufacturing Execution Systems (MES)
Warehouse Management Systems (WMS)
Application Infrastructure & Middleware
Blockchain
Data Exchange & Integration
Event-Driven Application
Middleware, SDKs & Libraries
Cybersecurity & Privacy
Application Security
Cloud Security
Intrusion Detection
Network Security
Networks & Connectivity
Global Navigation Satellite System (GNSS)
NFC
RFID
Platform as a Service (PaaS)
Application Development Platforms
Device Management Platforms
Robots
Collaborative Robots
Wheeled Robots
Automation & Control
Human Machine Interface (HMI)
Use Cases
Additive Manufacturing
Autonomous Transport Systems
Behavior & Emotion Tracking
Building Automation & Control
Chatbots
Clinical Image Analysis
Construction Management
Cybersecurity
Demand Planning & Forecasting
Facial Recognition
Fleet Management
Fraud Detection
Infrastructure Inspection
Intelligent Packaging
Inventory Management
Last Mile Delivery
Leakage & Flood Monitoring
Leasing Finance Automation
Machine to Machine Payments
Manufacturing Process Simulation
Onsite Human Safety Management
Personnel Tracking & Monitoring
Predictive Maintenance
Real-Time Location System (RTLS)
Remote Collaboration
Smart Campus
Speech Recognition
Supply Chain Visibility
Tamper Detection
Time Sensitive Networking
Track & Trace of Assets
Traffic Monitoring
Transportation Simulation
Usage-Based Insurance
Vehicle-to-Infrastructure
Virtual Prototyping & Product Testing
Virtual Reality
Virtual Training
Functions
Human Resources
Logistics & Transportation
Maintenance
Procurement
Product Research & Development
Quality Assurance
Sales & Marketing
Warehouse & Inventory Management
Industries
Agriculture
Apparel
Automotive
Buildings
Cement
Construction & Infrastructure
Consumer Goods
E-Commerce
Education
Electrical Grids
Equipment & Machinery
Finance & Insurance
Food & Beverage
Glass
Healthcare & Hospitals
Life Sciences
National Security & Defense
Packaging
Plastics
Retail
Telecommunications
Transportation
Services
Cloud Planning, Design & Implementation Services
Data Science Services
System Integration
Testing & Certification
Training
Google Cloud Platform’s Technology Stack maps Google Cloud Platform’s participation in the infrastructure as a service (iaas), analytics and modeling, platform as a service (paas), networks and connectivity, robots, sensors, functional applications, cybersecurity and privacy, application infrastructure and middleware, and automation and control IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
    Actuators
    Sensors
  • Devices Layer
  • Robots
    Drones
    Wearables
  • Supporting Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
None
Minor
Moderate
Strong
Number of Case Studies63
BBVA: Leveraging Geospatial Data for Innovative Customer Services
BBVA, a global banking and financial services group, was faced with the challenge of adapting to the rapidly changing landscape of digital payments. The bank noticed a significant increase in mobile payments, particularly during the COVID-19 pandemic, with the percentage of customers using this method rising from 4.4% to 23%. As part of its digital transformation journey, BBVA aimed to offer its customers an exceptional range of services and a great banking experience. The bank was already using Google Maps Platform to help customers find their nearest branch or ATM locations, but it wanted to further leverage the potential of Google Maps Platform solutions. BBVA's mobile banking app was used by 71% of its customers in Spain, and was accessed more than 120 million times a month. The bank wanted to provide more information about each customer transaction to offer a better financial experience for digital customers.
Data-Driven Innovation in Insurance: A Case Study of Assurance IQ and Looker
Assurance IQ, a direct-to-consumer platform offering personalized health and financial wellness solutions, faced a significant challenge in its early days. The company's data team was small and struggled with a scattered internal view of the business due to disconnected reports in siloed tools. They were using Excel, SQL, and other in-house tools, but lacked a true business intelligence (BI) platform. This resulted in inefficient use of time and a lack of a complete real-time view of the business for decision-making. Leadership lacked critical insight, and there were constant challenges around trust and consistency of the data. The data team wanted to ensure that each team member was looking at the same clean, accurate data and wanted to empower employees to explore the data on their own. However, the visualization tool they were using lacked version control and standardization.
Bank BRI: Revolutionizing Financial Inclusion in Asia with Digital Banking
Bank Rakyat Indonesia (Bank BRI), one of the largest banks in Indonesia, was faced with the challenge of increasing financial inclusion among unbanked Indonesians. The bank had an ambitious target of having 84 percent of Indonesians participating in the banking system by 2022. However, the bank's legacy technologies were proving to be a hindrance in achieving this goal. Each of the bank's products had their own public APIs, which were difficult to manage, secure, and monetize. Additionally, the process of onboarding new partners using host-to-host and VPN technology was time-consuming, taking up to six months. The bank also faced the challenge of reaching a largely rural population, with an estimated $8.3 billion in currency being held outside the banking system.
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