import pandas as pddf = pd.read_excel('data.xlsx')df.groupby('region').sum()model.fit(X_train, y_train)import numpy as npplt.plot(forecast)df.dropna(inplace=True)from sklearn import metricsprint(df.describe())np.mean(returns) * 252

Data · Insight · Power

Luminex Analytics Data Analytics Services

Custom KPI dashboards, predictive analytics, data cleaning and Excel automation — built around your business goals and data challenges.

Luminex Analytics logo

Business Analytics Services

Explore dashboard development, forecasting, data engineering, marketing analytics, financial reporting and automation.

Why Luminex?

We are a team of data scientists, engineers and strategists helping businesses of every size turn information into growth. From your first dashboard to full AI forecasting, we guide you across the whole data galaxy.

Live Dashboard Demo

Illustrative sample data · Not client results

+181%
Year-over-year
JFMAMJJASOND

Our Expertise Map

Six capabilities, one team. Every engagement draws on the full spectrum.

  • Visualization95%
  • AI / ML88%
  • Engineering92%
  • Finance85%
  • Growth90%
  • Automation94%
VisualizationAI / MLEngineeringFinanceGrowthAutomation

ROI Calculator

See how much time automation could save your team.

Estimated yearly savings
$93,600
Assumes 60% of manual work automated

Client Results

Retail chain
+32% revenue

Unified POS and e-commerce data into one live sales dashboard.

SaaS startup
-45% churn

Built churn-prediction models that flagged at-risk accounts early.

Logistics firm
120h saved / month

Automated weekly Excel reporting with Python pipelines.

"Luminex turned our messy spreadsheets into decisions we trust."

— Operations Director

"The forecasting model paid for itself in the first quarter."

— Head of Finance

Ready to launch?

Tell us about your goals and data challenges.