Ingress/Case Studies/Tableau Enterprise BI

From plant-floor Excel to enterprise BI.

A Fortune 500 manufacturer with 8,000 employees across 12 plants operated in reporting silos, each location managing its own Excel-based dashboards. We unified operations, finance, and supply chain reporting on a single Tableau Server platform, automating data flows from SAP and enabling self-service analytics for 400+ users.

Enterprise ยท Data Analytics 6 months Tableau ยท SAP ยท Python ETL
Live Users Onboarded
400+
Operations, finance, supply chain managers
Reporting Automation Gain
85%
Manual Excel work eliminated
Context

Fragmented reporting, unified opportunity.

The client operated 12 manufacturing plants across North America, each generating its own operational, financial, and supply chain reports in Excel. While each plant's reporting was accurate, leadership had no consolidated view of inventory turns, production efficiency, or margin performance across the enterprise. Month-end consolidation took weeks and required manual reconciliation by the finance team.

The company had already invested in SAP ERP and wanted to leverage the data asset they were generating. They needed a modern BI platform that could scale to 400+ users, provide self-service analytics, and reduce the operational burden on their finance and operations teams.

  • Data silos across plants. Each location maintained separate Excel dashboards with no single source of truth for enterprise KPIs.
  • Manual month-end process. Finance team spent 3 weeks consolidating plant reports and reconciling discrepancies by hand.
  • Limited scalability. Excel-based reporting couldn't support the level of detail needed for operations teams to make real-time decisions.
  • Untapped SAP investment. ERP system was generating rich data, but it wasn't being leveraged for analytics or strategic reporting.
Approach

How we built it.

We implemented a three-layer architecture, starting with a rigorous data inventory to map all reporting sources, building automated ETL pipelines from SAP, then deploying Tableau Server with governance, role-based access, and a structured training program.

01.
Data Inventory & Modeling
Audited all existing Excel reports, identified KPIs, and designed normalized dimensional models for operations, finance, and supply chain domains.
SAP AnalysisData Architecture
โ†’
02.
SAP Connector & ETL Build
Built Python-based extraction pipelines from SAP BW and transactional tables, landed data in SQL Server staging, and automated nightly refreshes with error handling and reconciliation logic.
Python ETLSAP BW
โ†’
03.
Tableau Server Deployment & Governance
Deployed Tableau Server on-premise with 6 content collections, published standardized dashboards for operations, finance, and supply chain, and configured row-level security by plant and role.
Tableau ServerRLS
โ†’
04.
User Onboarding & Training
Trained 400+ users across all plants on dashboard navigation, self-service filters, and best practices for analytics. Provided train-the-trainer resources for local IT teams to support ongoing adoption.
TrainingAdoption
โ†’
Outcomes

What it delivered.

85%

Reporting automation

Manual Excel work eliminated through automated data pipelines and self-service dashboards. Finance team reallocated from consolidation to strategic analysis.

24 hrs

Data freshness improvement

Real-time and near-real-time dashboards replaced weekly Excel refreshes. Operations teams now make decisions on current data, not one-week-old snapshots.

400+

Active users enabled

Democratized analytics across all 12 plants. Operations, finance, and supply chain teams all self-service, reducing BI team bottlenecks.

Tech Stack

What we used.

๐Ÿ“Š

Tableau Server

Enterprise BI platform with on-premise deployment, row-level security, and governance across 6 content collections.

๐Ÿ”—

SAP BW Connectors

Real-time and batch connectors to SAP transactional and BW data, enabling unified source of truth from ERP.

๐Ÿ

Python ETL

Orchestrated extraction, transformation, and load pipelines using Python, with error handling and reconciliation logic for data quality.

๐Ÿ—„๏ธ

SQL Server

Enterprise data warehouse hosting normalized dimensional models and supporting live Tableau semantic layer and reporting.

Start a conversation

Tell us what's worth doing.

// 30 minutes โ†’ a written brief.

Bring the problem. We'll come back with a written brief, what to build, what to defer, and where AI actually moves the number. No deck pitches.

Emailconnect@ingressits.com
GSA MAS#47QTCA26D000K
Reply< 24 hrs