Data Lake Implementation for a Big5 Consulting Firm
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Education
- Equipment & Machinery
Use Cases
- Movement Prediction
- Predictive Maintenance
Services
- Data Science Services
- System Integration
The Customer
Not disclosed
About The Customer
The customer is a part of a global network of professional services firm providing audit tax and advisory services. They are part of the Big5 consulting firms and have operations carried out in Australia. As part of their digital transformation journey, they were looking for a partner to help them with a technical proof of concept on Cortana analysis suite (CAS’s) data lake set of offerings. Their needs were centered around data consolidation, analytics, scheduling, and data organization.
The Challenge
The customer, a global network of professional services firm providing audit tax and advisory services, was looking to digitize their business operations. They were in need of a partner to do a technical proof of concept on Cortana analysis suite (CAS’s) data lake set of offerings. The customer's needs included bringing in data from multiple cloud tenants into a single location, running descriptive and predictive analytics on those data, establishing a regular schedule as well as data organization for the above, and the need for one consolidated version of data points.
The Solution
Aspire Systems conducted a detailed analysis and brought in the data from different sources into Data Lake Store using Data Factory. They used U-SQL for Descriptive, and Azure Machine Learning (ML) for Predictive Analytics, combining the power of Declarative(SQL) as well as Imperative(C#) programming. Azure Data Factory was used to create multiple Data pipelines for data orchestration and scheduling. Cortana analysis suite (CAS) provided an integrated set of components, and Azure ML provided an extensive and extensible set of algorithms, reducing the need to look for an external source.
Operational Impact
Quantitative Benefit
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