Insights

Drive better business decisions

Turn data into business opportunities and drive better business decisions across your organization with the help of BI. Your data can become your business’ asset, and by getting to know your business’ strengths and weaknesses with actionable metrics, you can ensure competitiveness and profitability.

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Features

Intelligent insights

Grow your business by analyzing deep data, sharing AI insights, and keeping the metrics in one place- updated in real-time, across all devices.

Live dashboards

Keep your dashboards updated in real-time by streaming data from factory sensors, social media sources, service usage metrics, and much more.

Customizable BI

Customize your Power BI report, picking your preferred visual theme from the visualizations panel, and present data in a way that fits your business best.

Data visualization

Publish, edit, update, share, and un-share your visualizations in blog posts, websites, emails, or social media on any device.

Microsoft integrations

Collaborate with your colleagues on dashboards, reports, and datasets to create apps with the help of Power BI app workspaces.

Power BI mobile

Take profit of the Power BI advantages by leveraging mobile apps set for iOS, Android, and Windows 10 mobile devices.


Type of analytics

Descriptive analytics

Descriptive analytics answers the question “what happened?”. In a retailer or brand setting for instance they can answer common questions such as “how many vouchers were redeemed?”, “how do my stores perform?”, “what are the demographics of my customers?”.

Diagnostic analytics

Diagnostic analytics answers the question “why did it happen?” by providing deeper analysis, correlation, and causality. For example, in the retailer or brand setting, they can point out that the sales were increased because the 1+1 free item promotion increased the average basket of the customers.

Predictive analytics

Predictive analytics predicts what will happen in the future. By leveraging the ML power, you can create predictive models, feed them with historical data, and use them to predict the future. A retailer could forecast his sales or find as early as possible the VIP customers by predicting customer spending.

Prescriptive analytics

Prescriptive analytics answers the question “What should we do about it?”. It suggests various courses of action and outlines what are the potential implications and results for each one. In a retailer setting the system could suggest that you will need more staff during specific hours to handle the extra customers coming into the store.


Case studies

Find out more about our success stories and how our customers made the most out of our services.

Case studies

  • VODAFONE

    February 19, 2020 Vodafone

    It reliably supports the daily needs of consumers and businesses and actively contributes to the economic and social development in Greece.

  • KAFKAS

    February 18, 2020 kafkas

    In light of its constant development, Kafkas S.A. needed an effective customer relationship management system (CRM).

  • Schneider Electric

    February 10, 2020 Schneider

    "i-NRG4U reward program. 70 POS covered produced 1000+ registrations, from diffused markets".

  • VERO SA

    February 10, 2019 Vero sa

    "An omnichannel approach, introducing, not only a traditional card, but also a mobile app and a microsite".


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