To engage in proactive field maintenance and service delivery, The Company heavily invested in modern tools and technologies for telematics and predictive analytics. In addition, since The Company depends heavily on part data from the field for predictive analytics, it invested in field sensors and big data technology.
All this data, captured several times an hour, is then streamed or transferred into a data lake. The company needed an agile data integration and access layer, one that can easily integrate big data with other sources of enterprise or cloud data in real time.
Download this case study to learn more about the following:
- Why traditional data integration methods fell short of The Company's requirements.
- How The Company used data virtualization for multiple enterprise-wide projects.
- How data virtualization helped The Company optimize customers' asset performance.
- How The Company enjoyed a twofold boost in revenue.
- How The Company have enhanced their insight into part failure rates.
