Augmented Analytics

Automated insight generation and machine-assisted data analytics

Boardwiser NLG blue header edition

Why Augment Your Analytics

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Automated Tasks

Machine-learning-driven data preparation, insights and visualizations give analysts a head start.

This drives productivity and innovation as experts can focus on higher value-added tasks.

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Enhanced Insight Discovery

Context- and usage-aware insight and data source curation direct human attention to actionable data.

This improves decision quality at all organizational levels with complete and accurate insights.

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Conversational Analytics

Intuitive, human-like interfaces drive engagement with data and help users of get to insights faster, regardless of technical proficiency.

This increases platform engagement and scalability both horizontally and vertically.



AION combines AutoML and data science to offer customers a robust platform for applying machine learning to real-world problems. It provides customers with the capability to rapidly build prototypes for solving business problems.

Boardwiser NLG

Best-in-class machine learning and natural-language generation (NLG) ensure that relevant driver factors behind KPI changes are detected and communicated without the need for manual analysis. It automatically and accurately identifies report-worthy outliers and summarizes them for easy subsequent analysis and reporting.

Topic Modeling

A flexible solution for the analysis of large volumes of text-based data to unlock insights that are otherwise difficult to extract and understand for humans. Read this white paper to get a working understanding of topic modeling and get implementation tips.

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Ask the Expert

Eszter Windhager-Pokol

Head of Data Science

Eszter has years of experience supporting data-driven decision-making as a consultant, researching collaboration filtering and developing user behavior analytics products. As the head of data science at Starschema, she has overseen projects implementing augmented analytics solutions at a variety of large organizations.

Windhager Pokol Eszter
Predictive Maintenance in Manufacturing

Data scientists and manufacturing specialists can examine production lines to determine what data can be used to predict future failures and how to best collect it. A recent (2018) report on the manufacturing industry saw 31% of manufacturing CEOs expecting artificial intelligence and machine learning to contribute to a reduction in operating costs. Learn how predictive maintenance helps make this reality.

Demand Forecasting with Latent Matrix Factorization

For many businesses, demand planning is essential. Profitability, cash flow, and customer satisfaction and retention all hinge on getting this right. This white paper will introduce latent matrix factorization to model demand curves and discuss how it can be used to achieve these outcomes.

Customer Segmentation at an Energy Company

Introducing a machine learning based segment view about your customers gives the opportunity to improve conversions and lower customer acquisitions. Learn more how a sophisticated segmentation model, based on your existing data, can increase the number of customer purchasing and your campaigns' success rate by 40%.

Fast, Actionable Financial Insights

Changes in the global business environment have driven a need for faster insights and decisions. In response to these changes, a global American software company approached Starschema about developing a solution for personalized, easily accessible and highly actionable financial insights.