By 2020, Mario Morales of IDC, estimates that devices embedded with sensors and network connectivity will create 40,000 exabytes of data. To harness this mass of information, it will be critical to efficiently prepare and combine data to deliver insights that drive the next generation of smart devices.
The exponential growth of connected devices continues to produce volumes of multi-structured data logs, which need to be wrangled and combined with traditional data to discover and predict the life and value of assets and improving product development.
To improve the customer experience, wrangle a variety of multi-structured customer data, including shopping history and physical movements through stores, which will better personalize recommendations and offers and, ultimately, drive topline growth. In addition, incorporating in-store RFID improves inventory tracking, reduces overhead, and ensures a reliable anti-theft system.
Vehicle sensors offer rich data to support large fleets, monitoring both vehicle and driver behavior. To reduce fuel consumption, optimize routes, reduce emissions and safeguard against accidents, wrangle hundreds of new data points, including speed, geocoding, mileage, and engine health.
Track product usage and improve decision-making by wrangling sensor and RFID data embedded in products, lounges, stores, bank branches, hotels, planes, and wearables with traditional demographic, mobile, and weather data. Actionable insights from wrangling complex, diverse data types help to monetize new services on top of existing products, expand into new territories with remote monitoring, and diversify into new revenue streams.
Translating detailed infrastructure log data into workable data takes a lot of extra IT cycles and slows the process considerably. Our teams use technology, including Trifacta’s solution, to reduce these cycles and enable product teams to work more closely.