INDEX

Wearable Data Analytics and Business Models

Table of Contents

  • 1. EXECUTIVE SUMMARY
  • 2. KEY RECOMMENDATIONS
  • 3. MARKET TRENDS
    • 3.1. Data Analytics in the IoT
    • 3.2. The Data that Wearable Devices Collect
    • 3.3. Wearable Data Analytics
    • 3.4. Wearable Data Monetization
    • 3.5. Wearable Data Challenges
    • 3.6. How Wearable Data Analytics Is Set to Change
  • 4. MARKET FORECASTS
    • 4.1. Methodology
    • 4.2. Key Forecast Findings
  • 5. KEY DATA ANALYSIS PLAYERS
    • 5.1. Accenture
    • 5.2. Arcadia Data
    • 5.3. Augmate
    • 5.4. Catapult Sports
    • 5.5. Emu Analytics
    • 5.6. EVO (Big Cloud Analytics)
    • 5.7. Plantronics
    • 5.8. PTC
    • 5.9. Salesforce
    • 5.10. Samsung Electronics
    • 5.11. Samsung SDS
    • 5.12. Sentrian
    • 5.13. Snowflake
    • 5.14. SOTI
    • 5.15. Upskill
    • 5.16. Vivametrica


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Data analytics is becoming more prevalent within the IoT, providing companies with actionable information based on the data that devices and sensors collect. Companies are increasingly turning to wearable devices to aid employees with their work, providing them with information and collecting data about the user. Wearable data analytics is enabling companies to gain insight into worker processes, patient vitals, and customer habits, allowing informative decisions to be made. This analyzed data is more advantageous than the raw data, which can often be overwhelming and uninformative.
 
This report examines how data analytics can provide companies with a further ROI from sensors and devices, including wearables. It covers data analytics in the IoT, the data that wearable devices collect and how that can be analyzed and monetized, challenges in the market, what is set to change, and key market players. Forecasts include Wearable Device Shipments by End-User Channel, Wearable Device Shipments by Region, Wearable Device Shipments by Device Type, Enterprise Wearable Device Shipments by Vertical, Data and Analytic Services Revenue by Region, and Wearable Device Revenue by Device Type.

Table of Contents

  • 1. EXECUTIVE SUMMARY
  • 2. KEY RECOMMENDATIONS
  • 3. MARKET TRENDS
    • 3.1. Data Analytics in the IoT
    • 3.2. The Data that Wearable Devices Collect
    • 3.3. Wearable Data Analytics
    • 3.4. Wearable Data Monetization
    • 3.5. Wearable Data Challenges
    • 3.6. How Wearable Data Analytics Is Set to Change
  • 4. MARKET FORECASTS
    • 4.1. Methodology
    • 4.2. Key Forecast Findings
  • 5. KEY DATA ANALYSIS PLAYERS
    • 5.1. Accenture
    • 5.2. Arcadia Data
    • 5.3. Augmate
    • 5.4. Catapult Sports
    • 5.5. Emu Analytics
    • 5.6. EVO (Big Cloud Analytics)
    • 5.7. Plantronics
    • 5.8. PTC
    • 5.9. Salesforce
    • 5.10. Samsung Electronics
    • 5.11. Samsung SDS
    • 5.12. Sentrian
    • 5.13. Snowflake
    • 5.14. SOTI
    • 5.15. Upskill
    • 5.16. Vivametrica