Customer was majorly working on multiple disparate data sources to gather their entire data. At this point, their data was more like information not understanding the significance and its use. Their entire data ecosystem was divided into three different datasets — Core Revenue Management System, internal system and Data coming from other platforms being used (Revenue Management Application, Salesforce, SAP).
The Customer team collaborated closely with Kasmo to build and deploy a utilities management system for accelerated decision making and extract timely insights.
By identifying different data quality challenges, we could leverage Azure Data Services, and implement Azure Data Factory pipelines. Data Lake was used to store and analyse the data, thus enabling Conservice to improve the quality of its data sources.
Customer wanted to focus on automating reporting and analytical capabilities. So, they are now considering new ways to use data storehouses. With data warehouse, and discovery capabilities of Azure, they can generate user specific experiences that bring together business and customer data to simplify the ways in which their customers can process revenue and billing.
Since Customer also wanted to forecast monthly revenues, Azure Machine Learning Service provided a way to predict numbers and values immediately. With it, they now have forecasted data for over five years.
Now, Customer can move “full speed ahead” with its data modernization goals by leveraging technologies such as Azure Data Services (ADF, ADLS, Databricks, Azure SQL, Synapse Analytics, Purview)
Looking ahead, they wanted focus more on increasing their business avenues, and spend less time in managing their incoming data.
To elaborate it further, here’s an interesting example on how they plan to generate more business insights. By adding a self-serving reports capability through which they can select various financial or operations attributes as per their need and create a completely customized report all on their own. Thus, allowing them to centralize, add features, and increase the speed to the changing requirements quickly.