Analytics SaaS Provider Scales Instantly, Delivers Faster and More Cost-Efficient Service to Customers
Customer Company Size
Startup
Region
- America
Country
- Canada
Product
- Azure SQL Database
- Azure Data Factory
- Azure Functions
- Power BI
Tech Stack
- Serverless Computing
- APIs
- Business Intelligence
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
- Analytics & Modeling - Big Data Analytics
Applicable Industries
- Professional Service
Applicable Functions
- Business Operation
Services
- Cloud Planning, Design & Implementation Services
- Software Design & Engineering Services
About The Customer
Inlitix is a small Canadian company providing software as a service (SaaS) business intelligence solutions, primarily targeting the small and medium business market. Founded in 2017, the company aims to offer affordable, scalable, and easy-to-use BI services. Inlitix focuses on interoperability across various enterprise resource planning (ERP) systems, providing out-of-the-box reporting and analytics solutions. The company leverages Microsoft Azure's serverless compute tier to automatically scale compute for its databases, ensuring quick performance response for 'bursty' workloads while maintaining cost efficiency. This approach allows Inlitix to refresh data faster, creating opportunities for more business insights and higher value for its customers. The company uses Azure Data Factory, Azure Functions, and Power BI to pull raw data, transform it into a common data model, and provide high-quality BI across a variety of business scenarios. Inlitix's innovative use of serverless computing enables it to balance cost and performance effectively, ensuring that it can meet the evolving data needs of its customers.
The Challenge
Most businesses generate a lot of data, but that data isn’t valuable for decision making if it’s not structured and analyzed. Analytics aren’t as effective if they are slow and expensive to produce. Inlitix was founded to offer a timely, easy-to-use, affordable BI as a service for small and medium-size businesses. They focused on interoperability across different ERP systems with different datasets and offered out-of-the-box reporting and analytics solutions. However, Inlitix found that it only needed more compute power at certain times, such as when it spins up development and QA environments or when production data is refreshed. It didn’t make sense to pay for a constant high level of compute resources during the times when they weren’t needed. To minimize the company’s compute requirements and maintain affordability, staff would manually adjust and optimize queries, which took time away from focusing on more strategic tasks and adding value to their application. Inlitix wanted to optimize the balance between cost and performance of its databases while ensuring it could quickly process data from customer ERP systems and refresh Power BI reports more frequently.
The Solution
Inlitix adopted SQL Database serverless to automatically scale the company’s compute capacity for its development, QA, and production workloads. This decision was based on the seamless interoperation that it could achieve between SQL Database serverless and its existing environment, which includes Azure Data Factory and Azure Functions. The company uses Data Factory to push raw data into SQL Database serverless, where it transforms the data to create well-structured, high-quality warehouse tables. Azure Functions are then used to launch a Power BI refresh from the data in SQL Database. By combining Azure and Power BI, Inlitix has created an end-to-end environment that works together well, and it’s easy to monitor performance and manage security. The serverless approach allows Inlitix to pay only for the compute it needs, as SQL Database serverless automatically scales compute based on workload demand and bills only for the amount of compute used per second. This has significantly reduced the company's development and QA environment costs and increased efficiencies by reducing manual database management. The serverless databases are configured to automatically pause when not in use, further optimizing cost savings.
Operational Impact
Quantitative Benefit
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