Capitalize on IoT Data with ThingWorx Analytics
The findings in a new research report called Trends vs Technologies from Capita Technology Solutions points to a lack of skills and understanding as two big factors that are holding back technology implementation, specifically in IoT and Big Data. In fact, 80% of survey respondents* indicated that they did not have the skills to capitalize on the data received from the IoT, despite a majority (88%) agreeing that financial gains can be made through adoption of new technology trends.
Historically, the discussions around IoT and Big Data have been vast and with few specifics. It can be difficult for a company to find a starting point, get a firm foothold, and execute a plan that shows results. IoT data, with its unique characteristics in volume, velocity, and variety, poses an extra challenge when viewed through the lens of traditional approaches to analytics.
For example, operational reporting is an often-used tool for traditional data analytics. It requires the aggregation and analysis of specific data sets that run on a set frequency. The challenge with applying this approach to IoT data is the variety of data coming from devices and inputs across the organization. Data that falls outside the pre-defined aggregations are not analyzed and included in the report.
So how can a company capitalize on their IoT data?
ThingWorx Analytics is the key to capitalize on IoT data without the need for specialized skills. ThingWorx Analytics is designed to add data science-like functionality to IoT solutions by those who are not data scientists, statisticians, or machine learning experts.
Automated analytics that are tightly integrated with your IoT platform means that every solution can have embedded analytics from the very beginning. By implementing the ThingWorx Platform with ThingWorx Analytics, you can have real-time pattern and anomaly detection, automated predictive analytics, and contextualized recommendations without the need for complex programming. Better yet, ThingWorx Analytics is designed for deployment on the edge, in data centers, or in the cloud – so it fits into almost any enterprise organization.
*The survey sample included 125 IT technology leaders across legal, finance, insurance, and manufacturing industries.