Technology & Software
India
End to End Project Lifecycle Management
The client struggled to deliver consistent, timely, and actionable reporting across business units. Key challenges discussed:
Scattered Metrics
KPIs were maintained in separate Excel sheets, resulting in inconsistent formats and metrics across teams.
Slow Decision Cycles
Manual consolidation of data caused delays, making it hard to act on insights quickly.
Limited System Integration
Existing reports weren’t connected to enterprise data sources like ET2000 and DMS, restricting scalability and broader analysis.
Isolated Data Stack
Sales, inventory, and retail performance data remained isolated, preventing cross-functional visibility.
Static Reporting
Reports lacked interactivity, no drill-downs, filters, or real-time updates, reducing their usefulness for operational decision-making.
Upon further discussions, DataToBiz implemented a comprehensive two-phase BI transformation workflow:
Phase 1: Rapid Excel-to-Power BI Development
Phase 2: AWS Data Warehouse Integration
Phase 1:
Phase 2:
Architecture & Data Integration
Dashboard Development
Data Automation
Performance Optimization
Faster Report Preparation
Automating Excel-based processes with AWS-powered pipelines cut report preparation time by ~50%, reducing manual effort from 8-10 hours per day to just 4-5 hours.
Real-Time Decision Making
Daily refreshed dashboards provided leaders with near real-time insights, improving decision-making speed by approximately 40%.
Consistent KPI Tracking
Standardized metrics and centralized dashboards ensured 100% alignment of KPIs across 6+ business units, reducing discrepancies and reporting errors by around 35%.
Scalability
AWS integration allowed the platform to handle 2-3x data growth without performance degradation, supporting future expansion to additional regions and datasets.
Improved Data Governance
Role-based access, standardized definitions, and audit trails covering 100% of dashboards and datasets strengthened governance, cutting compliance risks by roughly 30%.
By connecting Power BI with AWS data pipelines, DataToBiz helped the client shift from static, disconnected reports to a centralized, automated, and interactive BI system. This improved efficiency, cut reporting delays, and created a scalable analytics foundation for smarter, long-term decisions.
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DataToBiz is a good choice for someone who wants a partner who understands the product journey, requirements, and delivery expectations. They have the experience and agility to understand what’s possible and deliver to the client’s expectations. They‘re really passionate people, and they know what they’re doing!
We’re impressed with DataToBiz’s professionalism, dedicated support, and consistent follow-ups. Their team maintains clear communication through online meetings, ensuring a smooth and reliable collaboration.
A solution like this is a good fit if your teams spend more time collecting and reconciling data than acting on it, if reports from different departments do not match, or if decisions depend on delayed or manual reporting. It also fits when your data is growing in volume or sources, and your current setup struggles to keep up.
DataToBiz starts with a discovery call to review your goals, data sources, and reporting gaps. You get a clear view of the expected outcomes, effort, and timeline before any commitment.
Yes. Every solution DataToBiz delivers is configured around your industry, business processes, and existing data environment. The team assesses your current systems, data quality, and reporting needs first, then designs a solution that works with what you already have instead of replacing it. This applies across industries such as manufacturing, retail, healthcare, finance, and logistics, and across setups ranging from legacy databases to cloud data platforms.
DataToBiz works across the major analytics, cloud, and data engineering stacks. For BI and visualization, this includes Power BI, Tableau, and Looker. For cloud platforms, it includes Microsoft Azure, AWS, and Google Cloud. For data warehousing and processing, it includes Snowflake, Databricks, and SQL-based databases. Data sources include ERP and CRM systems, spreadsheets, APIs, IoT and sensor data, and third-party applications.
If your stack includes a tool not listed here, the team can assess compatibility during discovery.
Most projects with DataToBiz take from a few weeks to a few months. The timeline depends on how ready your data infrastructure is for the initiative and how many systems need to connect. Smaller solutions go live quickly, while larger programs roll out in phases so you see value early. After an initial discovery call, you receive a timeline with clear milestones.
Security and governance is part of the plan from the first conversation. DataToBiz works within your security policies and follows the regulations that apply to your industry. The project usually Access stays limited to the people who need it, and confidentiality terms cover the engagement from kickoff to handover.
The work does not stop at go-live. Your team gets a proper handover and guidance on using the solution, and DataToBiz stays available for questions and improvements. The business impact of the project is measured against the goals set at the start, so you can see exactly what changed for your company.
