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DATA ANALYTICS. EVERYWHERE

With 44 zettabytes of data in the world, organizations are poised with the question: why do they need so much data if they don’t know how to use it? We know the answer.
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STEP UP ON A NEW LEVEL OF MANAGING YOUR DATA

  • Forecasting demand
    How will your sales be affected by season, time and other factors? Be flexible with your business processes.
  • Influencing your KPIs
    Use the full force of data and predictive analysis for forecasting your performance.
  • Optimizing your marketing
    Split your marketing budget according to verified data. Switch engagement channels and audience to achieve best results.
  • Investing into your customer intelligence
    Let your clients enjoy your services and products. Introduce new loyalty features and personalization options.

SUPPORTING YOU ACROSS THE FULL ANALYTICS LIFECYCLE

  • Business Intelligence
    Business Intelligence

    Business intelligence (BI) is a key data-driven process of understanding your business. It helps organizations make better decisions based on real-time information by displaying current and historical data on their operations. Reporting available in BI systems allows companies to keep track of their performance and make better-informed decisions.

  • Data Warehousing
    Data Warehousing

    Data Warehouses are a vital component of business intelligence. A data warehouse stores data from multiple sources in a single location. New data can be periodically added by people across organization thus becoming a library of historical data to be retrieved and analyzed in order to inform decision-making in the business.

  • Data Governance
    Data Governance

    Data governance is a concept that ensures data is secure, private, accurate, available, and usable. It includes all the actions employees should take, the processes they should follow, and the technology that supports them throughout the data life cycle (Data Quality, Data Lineage, Business Glossary, etc.).

  • ML and Big Data
    ML and Big Data

    Solutions based on ML and Big Data can generate insights from raw data. These tools are used in a number of cases to forecast demand and customer behavior, prevent fraud and raise sales efficiency.

ACCURATE DATA IN ALL VERTICALS

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