Manufacturing & Industrial Engineering
Australia
End to End Project Lifecycle Management
When we first sat down with the client’s team, the challenge was not simply about adding another reporting layer. Their analytics environment had evolved over time, and the growing volume of enterprise data and BI requirements was exposing gaps in how data was integrated, standardized, governed, and consumed.
Disconnected Enterprise Data
Data from NetSuite ERP and other enterprise systems needed to be brought into a common analytics environment. Without a unified data layer, cross-functional reporting depended on data being integrated and prepared consistently across sources.
Inconsistent Business Metrics
Different reporting requirements made standardized KPIs, calculations, and definitions increasingly important. The client needed a consistent way to structure business metrics so teams could work from the same numbers across reports and functions.
Scaling BI Requirements
As more teams relied on analytics, the environment had to support self-service reporting and expanding BI use cases without creating separate reporting processes or increasing dependence on manual data preparation.
Limitations in the Existing Architecture
The analytics setup needed to mature into a scalable cloud-native architecture that could handle data ingestion, transformation, storage, and analytics as connected parts of the same environment.
Growing Governance Needs
A broader analytics ecosystem also meant greater attention to data access, security, governance, and performance. The client needed these controls to be built into the environment as reporting expanded across the organization.
After understanding where the existing analytics setup was falling short, our experts focused on building a stronger data foundation first, then standardizing how that data was transformed, modeled, and presented to business users.
Unified Fabric Analytics Environment
Our team brought NetSuite ERP and other enterprise data into a centralized Microsoft Fabric environment, creating a common foundation for enterprise reporting and analytics.
Structured Data Architecture
We introduced a Bronze-Silver-Gold Medallion Architecture to move data through defined stages of ingestion, transformation, and business readiness, making the data easier to manage and reporting more consistent.
Stronger Enterprise Data Foundation
Using Microsoft OneLake, Fabric Lakehouse, and Fabric Data Warehouse, our engineers created a scalable structure for storing, transforming, and serving enterprise data across reporting workloads.
Standardized Power BI Reporting
We developed 50+ Power BI dashboards and reports covering finance, sales, operations, inventory, and executive performance, giving teams a more consistent view of business data.
Governed Business Intelligence
Our team implemented Power BI semantic models, standardized KPIs, DAX measures, and Row-Level Security (RLS) to maintain consistent business definitions while controlling access to sensitive information.
Foundation for Future Analytics
We also worked toward governance, security, monitoring, and deployment practices, preparing the analytics environment to support growing self-service requirements and future data initiatives.
The solution combined NetSuite, Microsoft Fabric, and Power BI into a connected technology stack, with each component handling a specific stage of the reporting process.
Data Sources
NetSuite ERP supplied core finance, sales, CRM, inventory, and procurement information, alongside other enterprise sources where required.
Data Ingestion
Microsoft Fabric Data Pipelines automated scheduled data transfers from NetSuite and other connected systems.
Data Lake
Microsoft OneLake and Fabric Lakehouse stored and organized information using a Bronze-Silver-Gold structure, separating raw, refined, and curated datasets.
Data Processing
Fabric Notebooks and Apache Spark handled cleansing, transformations, business rules, and KPI calculations before the data reached reporting layers.
Data Warehouse
Microsoft Fabric Data Warehouse provided structured datasets for enterprise and cross-functional reporting.
BI Modeling
Power BI Semantic Models and DAX defined shared metrics and calculations, while Row-Level Security (RLS) restricted data based on user access.
Reporting & Visualization
Added 50+ interactive dashboards to the system spanning finance, sales, operations, inventory, and executive performance.
Security & Governance
Microsoft Entra ID, access controls, data lineage, and encryption provided identity management, traceability, and protection across the platform.
Consistent Business Reporting
The implemented 50 visualization dashboards helped align finance, sales, operations, inventory, and leadership reporting patterns, making it easier for teams to work from a common business view.
One View of Business Performance
Streamlining enterprise data pipelines gave teams a more connected view of business performance instead of relying on information spread across different reporting sources.
Aligned KPIs and Metrics
Standardized definitions and calculations reduced differences between reports, helping teams interpret KPIs consistently across business functions.
Better Control Over Business Data
Stronger access and governance practices gave the organization greater control over who could view and use business information as analytics usage expanded.
Ready for Growing BI Needs
The client now has a stronger base for expanding self-service analytics, reporting requirements, and advanced data initiatives without having to rebuild the reporting foundation each time.
For the Australian technology and communications provider, DataToBiz set up a clearer path from enterprise data to business reporting with NetSuite, Microsoft Fabric, OneLake, and Power BI. The result was half a century plus of standardized dashboards, shared KPI definitions, tighter data controls, and an analytics setup that can keep pace with new reporting needs.
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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.
