Bulutistan

Turning cloud operations data into actionable visibility

Bulutistan worked with Deka Technology to consolidate operational data from APIs and databases into a reporting environment for infrastructure, service and invoicing processes. The solution combined a SQL Server data warehouse, SSIS pipelines and Power BI reporting for daily monitoring.

Primary service
Data & AI
Secondary capabilities
  • Cloud operations data

Project overview

Client
Bulutistan
Project focus
Operational monitoring, analytics and reporting
Data foundation
Microsoft SQL Server data warehouse with API and database ingestion
Reporting
Power BI dashboards supported by SSIS ETL processes
Operational coverage
Infrastructure, backup, incident, request and change data
Business-process connection
Analytics data supported related invoicing workflows

Challenge

Operational information was distributed across infrastructure, backup, incident, request, change and invoicing systems. Turning these separate data streams into a reliable operational view required consistent ingestion, transformation and reporting rather than manual consolidation.

Bulutistan needed to monitor high-volume daily activity while using the same data for service-management and finance processes. The reporting foundation had to connect technical operations with business workflows rather than create isolated dashboards.

Deka Technology role

Deka Technology designed the Microsoft SQL Server-based data warehouse and built ingestion pipelines for API and database sources. SSIS processes transformed and loaded the data, while Power BI reports made infrastructure and service information accessible for operational analysis.

The implementation covered virtual-machine resource usage, backup jobs, incidents, customer requests and changes. The source also reports that analytics data was incorporated into invoicing workflows for Bulutistan's 25 largest customers.

Approach

  1. Identify operational data sources

    Infrastructure, backup, service-management and invoicing data were mapped across APIs and databases.

  2. Create a central data foundation

    A SQL Server data warehouse provided a structured destination for the consolidated information.

  3. Build repeatable ETL pipelines

    SSIS processes handled ingestion and transformation; the source reports more than 25 data sources in the reporting environment.

  4. Develop decision-oriented reporting

    Power BI reports converted technical and operational records into usable monitoring views.

  5. Connect analytics with business processes

    The data foundation supported invoicing automation for the 25 largest customers alongside operational monitoring.

Outcomes

The source reports daily monitoring of more than 1,100 virtual machines and 1,000 backup jobs.

The source reports more than 100 work hours saved per month.

The source reports more than 25 ETL data sources feeding the reporting environment.

The source describes invoicing automation for Bulutistan's 25 largest customers.

The project established a shared analytics foundation for technical operations and related business processes.

Evidence note: All figures are reported by the archived project source. The source does not state the measurement method for monthly time savings or define “monitored” for the daily infrastructure figures.

Technology

  • Microsoft Power BI
  • Microsoft SQL Server
  • PostgreSQL
  • SQL Server Integration Services
  • C#

Deka Technology

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