Data Analytics Platform Examples for Businesses

Businesses collect more data than ever through CRM systems, marketing platforms, production software, and financial packages, but turning that fragmented data into actionable insights remains a persistent challenge. Standard BI tools offer generic charts and tables but often lack the flexibility to combine data from multiple sources, perform company-specific calculations, and present KPIs the way your team actually needs them for daily decision-making. The core problem is that data in isolation has limited value: only when sales data, operational metrics, and financial figures come together in an integrated view do the insights emerge that lead to better decisions. A custom analytics platform aggregates data from all your systems, transforms it into relevant metrics with business-specific formulas, and presents insights in dashboards that directly lead to action. MG Software builds analytics platforms for businesses that are serious about working in a data-driven way, from marketing and production to finance. Below we present three examples from diverse sectors that demonstrate how a custom analytics platform makes the difference compared to generic BI solutions.

Marketing analytics dashboard for e-commerce

An e-commerce company with a marketing budget of 50,000 euros per month spread across six channels had no central overview of return on ad spend (ROAS) per channel. Marketing managers had to log into Google Ads, Meta Ads, their email platform, and Google Analytics daily to gather results and manually combine them in a spreadsheet. This not only cost hours per week but also led to outdated decisions because data was always a day behind reality. We built a marketing analytics dashboard that automatically aggregates data from all channels via API connections, normalises it into a uniform data model, and presents it in a clear dashboard. The dashboard shows ROAS, cost per acquisition, customer lifetime value, and attribution per channel in real-time, with drill-down capabilities per campaign, product category, and time period. A budget optimisation module analyses historical campaign data and suggests how to redistribute the budget across channels for maximum return, accounting for seasonal effects and diminishing returns per channel. Weekly automatic reports with channel comparison and trend analysis are sent to the management team.

• Automatic data aggregation from Google Ads, Meta Ads, email, and Google Analytics in a central dashboard
• Real-time ROAS, cost per acquisition, and customer lifetime value calculations per channel
• Budget optimisation module generating redistribution proposals based on historical data
• Automatic weekly reports with channel comparison and trend analysis to the management team
• Result: ROAS improved from 3.2 to 4.8 through data-driven budget redistributions
• Integration via APIs with six marketing platforms and the e-commerce backend system

Operational BI platform for a manufacturing company

A manufacturing company with two factories and 15 production lines had no central insight into Overall Equipment Effectiveness (OEE) and other production KPIs. Data was scattered across PLC systems, ERP software, and manual Excel registrations filled in by operators at the end of each shift. Compiling a performance overview required hours of manual work and results were only available days later, too late to respond to problems. We built a BI platform that collects data from all sources via a data layer combining PLC signals in real-time, ERP data via scheduled synchronisations, and manual input via a user-friendly web form. The platform calculates real-time OEE per production line, broken down into availability, performance, and quality, shows downtime causes in Pareto charts for targeted improvement initiatives, and compares performance between production lines, shifts, and time periods. Operators see their line's current OEE on large factory floor screens and receive alerts for deviations that exceed a configurable threshold. The management team uses the platform for capacity planning and investment decisions based on historical performance data and trend analyses.

• Real-time OEE calculation per production line with data from PLCs, ERP, and manual registrations
• Pareto analysis of downtime causes for targeted improvement of the largest loss sources
• Performance comparison between production lines, shifts, and time periods with drill-down functionality
• Factory floor screens with real-time KPIs and alerts for deviations for operators
• Result: average OEE increased from 62% to 74% within eight months of implementation
• Data layer combining PLC signals via OPC-UA, ERP via REST API, and manual input via web form

Financial reporting platform for an accounting firm

An accounting firm with 85 SME clients spent over 200 hours monthly compiling financial reports. Each report required manual data extraction from accounting software, transformation to the desired format, supplementation with sector-specific benchmarks, and a visually appealing layout in PowerPoint or PDF. Due to the manual process, reports were not always consistent and rounding errors occurred regularly. We built a reporting platform that automatically retrieves data from clients' accounting packages via API connections, normalises the figures into a standard data model regardless of the source package, and presents them in standardised but client-configurable reports with a professional brand identity. The platform calculates financial ratios such as current ratio, solvency, and profit margin, compares them with sector averages from national statistics, and flags deviations requiring attention with colour coding. Reports are automatically generated as PDF and as an interactive dashboard that clients can access via a secured portal with drill-down capabilities down to general ledger account level. Account managers add a manual advisory note before the report is sent to the client, supported by automatic suggestions based on the detected deviations.

• Automatic data extraction from multiple accounting packages with normalisation to a standard data model
• Financial ratio calculations with comparison against sector-specific benchmarks
• Configurable report templates per client with consistent visual style
• Interactive client portal with drill-down capabilities alongside the generated PDF report
• Result: reporting time per client dropped from 2.5 hours to 20 minutes, 85% automatically generated
• Integration with Exact Online, Twinfield, Yuki, and Snelstart for multi-accounting software support

Key takeaways

• A custom analytics platform aggregates data from multiple sources and presents company-specific KPIs that generic BI tools cannot provide. Where standard tools are limited to the metrics the vendor has conceived, a custom platform calculates precisely the KPIs relevant to your organisation, with the formulas, time periods, and comparisons your team needs on a daily basis.
• Automatic data aggregation eliminates hours of manual data extraction and reduces the risk of errors in reports significantly. When data is automatically retrieved, normalised, and merged, the chance of copy errors, outdated figures, and inconsistencies between departments that inevitably occur with manual processing disappears entirely.
• Real-time dashboards on the work floor give operators and team leaders immediate insight into current performance and encourage proactive action on deviations. When a production line or campaign is underperforming, it becomes visible within minutes rather than at the next weekly report. This significantly shortens the response time to emerging problems.
• Benchmarking against sector averages makes it possible to objectively assess performance and identify improvement opportunities that remain invisible without a frame of reference. By placing your financial ratios, operational KPIs, or marketing metrics alongside industry peers, you immediately see where your organisation excels and where there is room for growth.
• Configurable report templates combine standardisation with client-specific customisations, so every report looks professional while simultaneously serving the specific information needs of the recipient. Your team can independently adjust templates, add new calculations, and modify layouts without depending on a developer for every change.
• A data layer that normalises multiple data sources is the indispensable foundation for reliable and consistent analyses. Without normalisation you are comparing apples with oranges: different systems use different date formats, currencies, units, and naming conventions. The data layer resolves these inconsistencies before data reaches the dashboards.

How MG Software can help

MG Software builds data analytics platforms that turn your business data into actionable insights your team uses daily to make better decisions. Our approach begins with an inventory of your data sources, current reporting processes, and the KPIs your organisation actually needs. We then design a data architecture with a normalisation layer that combines data from all your systems and transforms it into a consistent data model. Based on this model, we build dashboards your team can use intuitively, with drill-down capabilities, filter options, and comparisons across time periods and segments. From marketing analytics with ROAS calculations and channel attribution to production BI with OEE monitoring and downtime analysis, and from financial reporting with ratio calculations to benchmarking against sector averages: we build precisely the insights your organisation needs. Every platform includes automatic reports, configurable alerts, and export capabilities to PDF and Excel. Optionally, we build a client portal where your customers can view their own data. The timeline ranges from eight to fourteen weeks, depending on the number of data sources and calculation complexity.