Overview
A luxury hospitality group in Southeast Asia struggled to combine data coming from many systems and file types. Reports took days and delayed decisions. Krish Services Group built a modern analytics platform on Microsoft Azure. Leaders could view key business metrics within hours, helping teams act faster and manage properties more effectively.
Client Background
The client operates large number of hotels, resorts, and serviced apartments across Southeast Asia. Each property tracks occupancy, revenue, costs, and guest satisfaction using different tools and local systems. Data was spread across countries, languages, and formats, making it hard for leadership to get a single, clear view of business performance.
Challenges
- Data Silos Across Systems: Critical data was stored in flat files, SharePoint lists, and SQL databases, resulting in slow and error-prone reporting.
- Manual ETL Pipelines: Data was cleansed and combined manually in Excel, with no automation or lineage tracking.
- Delayed Access to Insights: Reports were refreshed weekly, which limited the ability to respond to performance changes in real-time.
Solutions
- Azure Synapse Implementation: We built a centralized SQL pool using Azure Synapse Analytics to ingest and manage data from multiple sources.
- Data Factory Pipelines and Cleansing: ADF and mapping data flows were used to automate transformations, deduplication, and quality checks.
- Power BI Dashboards: Visual dashboards enabled daily tracking of revenue, bookings, occupancy, and customer satisfaction metrics.
Technology in Use
Azure Data Lake
Azure Synapse Analytics
Azure Data Factory
Power BI
Business Value Propositions
- Faster Reporting Cycles: Reduced report refresh time from hours to a few hours, enabling same-day business reviews.
- Improved Data Governance: Established clear data controls and audit trails, improving trust and accountability for leadership teams.
- Wider Data Visibility: Enabled consistent access to key metrics across departments through centralized dashboards and reporting.
- AI-Ready Data Foundation: Created a structured data platform that supports future forecasting and advanced analytics initiatives.
Final Perspective
To facilitate quicker, data-driven operational and financial choices, Krish Services Group provided a scalable Azure analytics platform that unified complicated hospitality data, increased reporting speed, and offered leadership across hotels and resorts with timely, dependable insights.
Overview
A global energy services company collaborates with large facilities to utilize IoT sensors and track energy usage. As data volumes grew, their systems struggled to provide timely insights. They partnered with Krish Services to build an Azure-based analytics platform that turned sensor data into clear signals, enabling early action, lower costs, and better energy efficiency.
Client Background
The client is a global provider of smart energy services for industrial customers. They deploy sensors across buildings and equipment to track energy usage, improve performance, and support sustainability goals. Their focus is on helping organizations lower energy costs, reduce waste, and operate more efficiently across large, distributed environments.
Challenges
- Disconnected IoT Data Sources: Unreliable analysis and a lack of a trusted operational view due to sensor data arriving in different formats across sites.
- Delayed Real-Time Monitoring: Delayed visibility into energy spikes and device failures due to batch processing, causing higher costs, slower responses, and missed efficiency opportunities daily.
- Inability to Scale Data Processing: Legacy infrastructure could not handle growing IoT data volumes, restricting expansion, increasing risk, and limiting future analytics capabilities for the business.
Solutions
- Centralized IoT Data Platform: Built an Azure data lake with Databricks to ingest, clean, and analyze sensor data, enabling reliable anomaly detection at scale.
- Real-Time Operational Dashboards: Delivered Power BI dashboards showing live energy metrics across sites, helping teams spot issues faster and act quickly and confidently.
- Scalable Streaming Architecture: Designed a scalable Azure architecture to process millions of records daily, supporting alerts, growth, and future sensor expansion reliably and securely.
Technology in Use
Azure Data Lake
Azure Databricks
Azure Synapse Analytics
Azure Event Hub
Power BI
Business Value Propositions
- Predictive Maintenance Enablement: Early anomaly detection helped teams address equipment issues before failures, reducing unplanned outages and maintenance surprises.
- Lower Energy Waste and Downtime: Real-time monitoring reduced energy spikes and downtime, improving operational efficiency and controlling ongoing operational costs.
- Sustainability Visibility: Clear dashboards gave leaders visibility into energy usage patterns, supporting sustainability targets and carbon reduction initiatives.
- Future-Ready Data Platform: A flexible architecture allows easy onboarding of new sensors without redesigning systems or disrupting operations.
Final Perspective
We unified IoT data on Azure, enabling predictive maintenance and energy savings today, while preparing scalable analytics that will improve sustainability, reliability, and faster decision-making across future operations globally.
Overview
A large community services provider in Australia needed timely and accurate insights from its HR and payroll systems. We implemented a Microsoft Fabric data warehouse that combined data from several sources into one place. This decreased manual reporting, enhanced data accuracy, and gave leadership real-time visibility to support better decisions and compliance.
Client Background
Our client delivers aged care, disability support, and family services across several regions in Australia. Their HR and payroll data were spread across different systems, making reporting slow and inconsistent. Teams relied on manual spreadsheets to prepare reports, which increased effort and risk. They needed a more reliable and unified way to manage workforce data.
Challenges
- Inconsistent Workforce Data: HR and payroll data lived across multiple systems and APIs, making it difficult to create a single view for reporting and compliance.
- Manual and Time-Consuming Reporting: Teams relied heavily on spreadsheets and exports, spending hours preparing reports and validating numbers instead of focusing on operational work.
- No Real-Time Visibility for Leadership: Decision-makers lacked access to live workforce data, limiting their ability to track trends, respond quickly, and plan across regions and departments.
Solutions
- Modern Data Platform with Microsoft Fabric: Created a data warehouse (Microsoft Fabric) to securely ingest data from 19 Zambion Payroll APIs, enabling unified payroll analytics and real-time business insights through Power BI dashboards.
- Power BI Semantic Modelling: Star-schema models were built on top of the dataset to enable intuitive reporting and drill-down analytics.
- Governance and Security Controls: Implemented Microsoft Purview, Row-Level Security (RLS), and role-based access controls to maintain compliance with Australian privacy standards.
Technology in Use
- Microsoft Fabric
- Power BI
- Zambion APIs
- Azure Data Pipelines
- Microsoft Purview
Business Value Propositions
- Real-Time Workforce Insights: Leaders could access live HR and payroll data to plan staffing, budgets, and resource needs accurately.
- Faster Reporting Cycles: Reduced report preparation time from 12 hours to under 1 hour with automated pipelines.
- Stronger Data Governance: Improved data accuracy, audit readiness, and compliance with organizational governance standards through centralized controls.
- Self-Service for Leaders: Secure access to trusted reports and dashboards without relying on manual data requests.
Final Perspective
By unifying HR and payroll data into a governed, real-time platform, we simplified reporting, improved visibility, and helped leaders make faster, more confident workforce decisions.
Overview
A financial data consulting company needed to update its old reporting setup and moving to a Power BI environment that supports real-time data, secure access, and better visuals. The client partnered with us to modernize the reporting experience, make faster decisions, and enable simpler access for thousands of finance brokers.
Client Background
The client creates analytical platforms and app-based financial tools. These help businesses check performance, compare with industry benchmarks, and make smart decisions. Businesses use their data solutions to check financial outcomes and improve growth plans.
Challenges
- The existing SSRS reports were basic, with limited interactive capabilities and limited visualization options.
- KPIs and filters were fixed and not dynamic; hence, users were unable to explore or modify views to examine business metrics from various perspectives.
- The report design and layout were outdated and did not support real-time data updates.
Solutions
- Built Power BI reports with direct, live connections to SQL Server data sources for real-time data visibility and up-to-date insights.
- Added industry benchmarks and top performer comparisons to dashboards. This helps users compare their performance with market leaders.
- Facilitated secure collaboration through Power BI license management and guest user access, ensuring proper stakeholder engagement with controlled data security.
- Designed modern, outcome-focused dashboards that prioritize visual clarity and intuitive usage to enhance the effectiveness of decision-making.
Tech Stack
The project used a combination of modern Microsoft technologies to ensure scalability, performance, and security.
- SQL Server 2014 and SQL Server 2022
- Power BI and Power BI Admin Portal
Business Values
- The company was able to update its financial reporting into a usable business asset through the new Power BI-based solution.
- Assisted the Bank of New Zealand with the organization’s successful Data Mining App services.
- Lifted collaboration across 17,000+ finance brokers through a robust license management framework utilizing Azure AD.
- Improved the report usability and visualization with Power BI’s dynamic data modeling.
Future Scope
We plan to help the client move toward a broader intelligent analytics framework. The next steps include forecasting models, automated data refresh using Power BI Service and Azure, and role-based dashboards for executives, analysts, and brokers.
