Services — Data & Analytics
Data & Power BI
We connect the systems your data already lives in, model it properly, and build Power BI reporting each team actually opens. Including live pipelines from the ERP platforms most reporting projects get stuck on.
What we deliver alongside the dashboards
Reporting fails more often on the plumbing and the ownership than on the charts.
- Governed data model
- Automated pipelines
- Reporting per role
Technology
Sources, pipelines, and the reporting layer
Two lists are kept apart on purpose. The systems we have integrated are ones we have built pipelines against in client work. The connectors are platforms Power BI reaches natively, listed so you can find your own stack, not a claim that we have worked on each one.
Reporting
- Power BI
- Power BI Embedded
- DAX
- Semantic models
- Row-level security
- Paginated reports
Systems we have integrated
- NetSuite
- SAP Business One
- Microsoft Dynamics 365
- Epicor
- SYSPRO
- Deacom
- QuickBooks
- Xero
Data platform
- SQL Server
- Azure SQL
- PostgreSQL
- Star schema modeling
- Data warehouse design
Pipelines
- Azure Data Factory
- Python
- Saved-search and file exports
- Scheduled refresh
- Failure alerting
Available through Power BI connectors
- Salesforce
- Microsoft Dataverse
- SharePoint
- Excel
- Snowflake
- Databricks
- Google BigQuery
- Amazon Redshift
- Azure Synapse Analytics
- Oracle Database
- MySQL
- Google Analytics
- Smartsheet
- REST and OData APIs
Reporting problems rarely look like reporting problems at first. The inventory analytics work in our case studies is the clearest example of where they actually live: the fix there was not a better dashboard but abandoning a slow ERP API, after which refreshes went from hours to minutes and the servers behind the old approach were switched off. The figures exist, but they arrive late, they disagree between teams, and assembling them costs somebody two days a month in spreadsheets. The pricing intelligence platform in our case studies is the version of this we know best: market data existed, but it reached buyers too slowly and in too many formats to act on, so the work was in the pipelines and the model rather than in the charts.
Our engagements cover the whole path. We inventory the sources, tell you plainly what the data can support, design a governed model where measures are defined once, build monitored pipelines that alert when a refresh fails, then build the reporting each role actually needs. We connect directly to SAP Business One, NetSuite, Epicor, Deacom, Microsoft Dynamics 365, and SYSPRO, and we build pipelines against custom and older systems where no connector exists.
The last stage is the one that decides whether any of it survives. You get a documented model, naming conventions, and training, so next quarter's question can be answered by your team rather than by another engagement.
What separates reporting that gets used
Connected to the real sources
Direct integration with your ERP, CRM, finance systems, databases, and APIs, so reporting reflects the systems of record rather than an export somebody remembered to run.
A data model, not just charts
A governed semantic model with defined measures and relationships, so two teams asking the same question get the same number.
Reporting per role
Operational views for the people running the day, summary views for leadership, and raw exports for analysts, from one model rather than three competing versions.
Refreshes you can rely on
Scheduled pipelines that are monitored and alert on failure, so nobody presents a dashboard that quietly stopped updating last week.
Access control and governance
Row-level security and role-based access, so people see the figures they should and sensitive data stays contained.
Your team can extend it
Naming conventions, documentation, and training, so adding next quarter's report does not require calling us.
Our Power BI engagement
- 1
Discovery and Data Assessment
Establishing what the data can support.
Source Inventory
Mapping every source, including databases, ERP systems, files, and SaaS platforms, and assessing the quality of each.
Business Requirement Gathering
Understanding the decisions each team needs to make and the measures that actually inform them.
Gap Analysis
Identifying missing data, quality problems, and governance gaps before any pipeline work starts.
- 2
Architecture and Modeling
Structure before the first dashboard.
Warehouse Design
A schema suited to your query patterns, reporting cadence, and expected growth.
Semantic Model
Measures, relationships, and calculated tables defined once, so reports stay fast and consistent.
Governance Framework
Naming conventions, documentation standards, and row-level security defined at the start rather than retrofitted.
- 3
Build and Deployment
Pipelines first, then the reports on top.
Data Pipelines
Automated extract and load processes, tested, monitored, and alerting when a refresh fails.
Dashboard Development
Layouts built around the decisions each role makes, with drill-through to the detail behind every figure.
Mobile Layouts
Reporting that works on a phone, because approvals and checks often happen away from a desk.
- 4
Rollout and Enablement
Adoption is the deliverable.
User Acceptance Testing
Validation with the people who will use the reporting, against real scenarios, before go-live.
Training and Documentation
Role-specific sessions and reference documentation so your team can use and extend what we built.
Ongoing Support
Post-launch monitoring, refresh tuning, and additions as reporting needs change.
ERP and business systems we connect
SAP Business One
NetSuite
Epicor
Deacom
Microsoft Dynamics 365
SYSPROSAP Business OneNetSuiteEpicorDeacomMicrosoft Dynamics 365SYSPROSAP Business OneNetSuiteEpicorDeacomMicrosoft Dynamics 365SYSPROWant to see what your current reporting could tell you?
How a data engagement starts
- 1
A conversation about the decisions
We start with the decisions you need to make and the questions your current reporting cannot answer, not with a tool demonstration.
- 2
A look at the actual sources
We review the systems your data lives in and tell you honestly what they can support today and what needs work first.
- 3
A scoped plan with a full price
You get the architecture, the sequence, the timeline, and the total cost before committing to anything.
Why RothTech
Reporting projects usually fail in one of two ways. Either the dashboards look right but the numbers are assembled by hand upstream, or a consultancy builds something impressive and every later change has to go back through them. We build the pipelines and the model underneath, then hand over documentation and training so your team owns the reporting. Because we also build the systems the data comes from, connecting an ERP or a custom platform is familiar work rather than a discovery project.
Frequently Asked Questions
Related Case Studies
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Power BI Inventory & Sales Analytics for Retail
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