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Big Data

Modern technology to manage multi-dimensional data

BigDataBig Data is the latest technology that constitutes a breakthrough support in a modern business building model.

Making decisions is based on multiple sources today, both those stored in the internal resources of the company and those generated in the external environment. Skilful management and analysis of the obtained information can significantly improve the quality and duration of the decision-making processes realisation in the company. Thanks to that, your actions will not be random, and the decisions will result from the in-depth analysis of multi-dimensional data. The proper use of the information and IT technology support opens new opportunities to strengthen business processes in the enterprise.


Benefits from the Big Data class solutions:

  • Ability to take business decisions faster
  • Current and more precise risk assessment
  • Improvement of customer service quality
  • Ability to integrate information from various sources, including social media with information from informatics systems operating within the organization
  • Ability to handle information derived from unstructured data
  • Freedom for business scaling up to millions of transactions at the same time
  • Increased efficiency of billing and accounting systems
  • Ongoing analysis of trends and customer behaviour
  • Faster e-commerce systems reactions
  • Support for functioning analytical and reporting BI class solutions by equipping them with new possibilities to analyze massive amounts of data while adding multisectional analysis
  • Significant reduction of the waiting time for analyses and reports as well as the ability to conduct complex analyses in real time.


Areas of Big Data applications

  • Distributed search – how to find , visualise and understand all the information necessary to take the right decision
  • Better customer understanding – how to explain the customer behavior by obtaining Bronder information about their needs
  • Basket analyses – what products should be offered in promotions together . Are there any correlations between products . What is the cost and the introduction of a new product
  • Range analysis – how often and through which channels customers living near the shop buy selected products – what is the facility range
  • Loyalty and customer value over time How to increase profit by measuring customer sentiment and by maintaining its value
  • Risk reducing –how to recognise a state of emergency in real time and reduce it
  • Operational analysis – how to improve the efficiency of infrastructure use in the measurement data
  • Increasing of the data amount for analysis –increasing the efficiency of existing analytical platform


Modern approach to the problem – proposed solution

Advanced Business Solutions Sp. with o.o. has started partner cooperation in the field of Big Data  class with IBM, offering one of the most interesting, yet complex solutions, by which we are able to meet the business needs of the most demanding customers. The proposed solution ensures speed, easy use, scalability and efficient business analytics: no need to install software, lack of indexes and tuning, no need of data storage administration. Analytical platform is simple and user-friendly, tailored to the needs of managers managing different areas at different levels.

Among the elements that can constitute the components of the proposed Big Data solutions the following are included:

  • Pure Data System for Analytics Appliance
  • Pure Data System for Hadoop
  • Infosphere Dataexplorer,
  • Infosphere streams,
  • Infosphere Biginsights


Visualisation of information in the Big Data architecture


Użytkownicy – Users
Komentarze – Comments
Zaznaczanie –Selection
Współdzielenie – Sharing
Dane – Data
Systemy plików – Files systems
Systemy dziedzinowe – Domain-systems
Źródła RSS – RSS sources
Dane w „Chmurze” – Data in the „Cloud”
Źródła lokalne – Local data
Źródła zewnętrzne – External data
Platforma Big Data – Big Data Platform
Akceleratory –Accelerators
Strumienie – Streans
Hurtownia – Warehouse


  • Relationships search
    • Navigation and search
    • Connection to the data regardless of their location and sources
  • Analysis of structured and unstructured data
    • Visualization of relationships and data use motive
    • Analysed information identification
    • Users identification
    • Context of use identification
  • Sharing data
    • Enrichment of data on the basis of users’ knowledge
    • Creating personalized data views
    • Point for integration of Big Data with userd


Architektura – Architecture
Kolektor danych – Data collector
Analizy danych w locie – On data analyses
Wizualizacja – Visualisation
Kolektor danych – Data collector
Hurtownia – Warehouse
Archiwum Hurtowni Danych – Data Warehouse Archive
Archiwum – Archive
Wyszukiwanie i wizualizacja – Search and visualiation
Hurtownia – Warehouse
Dane strukturalne i niestrukturalne – Structural and unstructured data
Przyspieszenie analiz – Analyses acceleration
Platforma analityczna – Analytics platform

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