The management and analytics of the data comprises several levels typical of these sectors, covering all the phases from least to most difficult, but all of them useful depending on the actor involved.
Our work methodology for data management and analytics
01.
ACQUIRING
Data acquisition ranges from current solutions in the industry, those coming from automata (PLC), dataloggers for telemanagement systems or data acquisition systems (SAD), to the new options in sensors and communications that the IoT brings us.
02.
REGISTERING
Depending on the needs, data storage could be local in the company’s facilities or using the new Cloud options for large amounts of information.
03.
INTEGRATING
The integration of the different sources will allow us to draw conclusions from the data, achieving a complete vision and ending information silos.
04.
ANALYZING
The generated data obtains value when we have unified and contextualized it. Even more so when we relate them to each other directly (ratios) or through data mining techniques that allow us to discover associations and correlations.
05.
VISUALIZING
The visualization is based on our experience in SCADA supervision systems that allow us to see the status of the facilities in real time, as well as the alarm and historical log.
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We develop data management and analytics in these sectors
Industry
- Obtaining calculated ratios
- Obtaining industrial indicators (OEE, MBTF, MTTR)
Manufacturing Intelligence to unify production data, energies and production orders - Machine learning for early incident detection
Remote control of the water cycle
- Obtaining calculated ratios
- Business Intelligence to unify data from stations with administrative and GIS
Departments of your company that we help through data management and analytics
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Industrial Computing for the acquisition and unification of all the sources of your company. Decisions are easier if you have all the data.
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