Business Objectives:
One of the major customer is into Consumer Appliances associated with manufacturing on the home appliance products which are interconnected with IoT devices and they wanted to improve the experience for their customers. Their major needs are
- Improve the customer experience with IoT data.
- Collect the IoT data from different sources on the real-time basis.
- Getting the useful insight and key business driven KPI’s from those IoT data to improve the Customer Experience.
Challenges:
- Processing High Volume of Data
- Lack of Data Quality
- Choosing the best visualization tool
- Lack of data quality.
- Required more manual time to refresh and export the data based on their business needs.
- Performance issues to refresh the data.
- Repeating data quality concerns from stakeholders which were affecting the business
Solution Design:
- We have used real-time data capturing solution based on Azure Event Hub Technology to collect and process events in real time.
- Databricks to process the huge volume of data with the help of the spark framework to improve the transformation time and reduce the processing cost.
- Lack of Data Quality has been monitored before processing into the Data Lake and eliminated while processing into the spark.
- Resolved Manual Intervention time due to an increase in transformation and less manual effort in refreshing using spark.
- Visualization tools and technologies such as Qlik Sense and Power Bi to develop the Cohort Analysis report to track the Events data with high quality and fast performance.
Value-Driven Results:
- High assurance of Data Quality.
- Improved the Customer Experience with the analysis from the IoT data and by working with AI/ML models.
- Automated the process that earlier needs the manual intervention time from 15h per week to 2h per week which saved huge manual effort and increased productivity in other areas.
- The solution we proposed saved 30-40% of operational costs.