Improve with machine learning models, data analytics, and unbeatable reporting

We are your go-to company for data analytics, machine learning models, and business reporting.

Data analytics

Analyzing your data regularly is critical for stability and growth

Companies that base decisions on intuition instead of data are bound to make mistakes. Businesses and their environments constantly change. So does their data.

At Dattae, our predictive models turn your data into knowledge. They empower organizations to make informed decisions and gradually improve performance with the support of our reporting models.
We design custom dashboards and key performance indicators (KPIs) that identify growth opportunities. We love trend analysis and uncovering patterns that help optimize processes.

We reveal the “why” behind your results. From market research and customer segmentation to product profitability analysis, we provide a clear view of your business.

Machine learning

Unsupervised machine learning models: when you need to uncover hidden patterns

We can predict customer churn rates to target retention campaigns or detect fraud patterns in your operations, automatically segment your customer base to personalize promotions, detect anomalies in industrial processes before they become critical issues… the possibilities are endless.

In general, we classify unsupervised machine learning models into three main groups:

  1. Clustering algorithms: group data into similar clusters
  2. Dimensionality reduction: reduce data complexity while preserving critical patterns
  3. Gaussian mixture: detect unusual patterns or outliers

Supervised learning models

Predict outcomes and improve efficiency in your business

Supervised learning models are a branch of machine learning in which algorithms learn patterns from labeled historical data.

These predictive models allow you to make reliable forecasts about future behavior and trends. We’ve implemented them across industries to better understand future consumption, revenue, costs, and expected sales volumes.

Regressions, decision trees, random forest, gradient boosting, neural networks… We use a broad set of models depending on your specific business challenge.

MLOps

MLOps: how we take a model idea to production

Building models must be a structured process, with clear objectives and a defined use case. Our process is straightforward and effective:

  1. Define the problem
  2. Gather and understand the data
  3. Explore and prepare the data thoroughly (this is where most of the work lies!)
  4. Test different modeling approaches
  5. Evaluate the solution and analyze key variables
  6. Present results, deploy the model into production, and monitor its performance

We ensure traceability and scalability so that your machine learning solutions are reliable and adapt to your business pace. Continuous monitoring ensures the model’s performance and accuracy remain aligned with initial expectations.

Reporting models

If you want to understand what's happening and anticipate competitors, you need reporting models

One of the most crucial aspects for any company is understanding and controlling what’s going on. Beyond having structured data or predictive models, it’s essential to have a reporting system that periodically informs you about your business performance—costs, sales, resource usage, market trends, and competitors.

A major weakness we see across industries is the lack of automation in reporting systems. Many processes are still manual, costing valuable time and resources.

There are many tools available for reporting, including:
(i) Power BI (ii) Tableau (iii) Qlik Sense (iv) Google Looker Studio (v) Metabase (vi) Domo (vii) Excel

Let’s talk and we’ll help you choose the best options for your company!