Data Analytics Consulting
Gain new insights from your process data
Data plays an increasingly important role in process industries as a lever to increase process efficiency, reduce downtimes, and optimize maintenance and service. The key to use the power of data is data analytics. This applies to companies of any size, but often small and medium-sized enterprises (SME) don’t have enough access to data scientists and machine learning experts. That makes evaluating historical data difficult.Instead of building a team of experts in-house, our Data Analytics Consulting approach provides data analytics as a consulting service for your company.
The findings together with recommendations for further investigation or implementation in a software application are presented in a final report. You will receive quick data analytics results and proof of concept studies without the need to employ dedicated data scientists.
What you will get
- Data analytics workshop together with you to specify data analytics use case
- Identification and prioritization of data analytics tasks
- Import and inspection of data collection
- Data preparation and analysis
- Data analytics report
- Presentation and visualization of findings and recommendations
- Next steps proposal (i.e. further analysis, software application development)
Many companies in the process industry are creating huge amounts of data but are having a hard time to use them for further optimization of processes, maintenance, and services. Data analytics is not their core business and setting up the required IT expertise can be expensive, so the question is: How can historical data be evaluated in order to find actionable insights from hidden cause-and-effect relationships, correlations, and patterns?
The answer is our Data Analytics Consulting Package for process industry.
Data Analytics Consulting Package:
- Discuss available data sources and process context (i.e. P&ID diagrams, physical models) with customer domain experts
- Identification and prioritization of potential data analytics use cases (i.e. condition monitoring, process optimization)
- Check available data collection regarding quality and suitability for the given task
- Prerequisite: good quality data as determined in the workshop
- Data management and preprocessing (Data interpolation, Feature selection)
- Data analytics and visualization (Visual analytics, Clustering, Correlations analysis, Regression, Anomaly detection)
- Regular feedback sessions with customer