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Big Data Solutions

Discover what our data scientists are capable of when solving your business challenges with Big Data, AI, Machine Learning, BI among other technologies.

Data is everywhere and in the amount that is often incomprehensible with traditional statistical methods. Learn how AI, Deep Learning, NLP, Geospatial Analysis can you help you achieve critical milestones in your organisation.



Case study

SCADA Business Connector

The client’s challenge was how to correctly predict system malfunction from one of its refinery process machines. See how we improved machine’s utilisation costs by 30%!

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Other case studies

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Industries that we helped with our data science expertise
 


We help our clients perform better in the following areas


Business Intelligence - Advanced Business Intelligence and Dashboard design capabilities:

  • BI & EPM Platform implementations
  • API integration connecting platforms with data marts and sources
  • Conduct QA, SIT and UAT test
  • Development of BI & EPM tools
  • BI Platform configurations
  • KPI dashboards implementation
     

Artificial Intelligence:

  • Development of Artificial Intelligence models including but not limited to: Deep Learning, Neural Networks, Random Forest, Support Vector Machines, Decision Trees and more,
  • Supported technologies include: R, Python, TensorFlow, SciPy, Keras, Theano and more,
  • A highly qualified team of Data Scientists and Data Engineers,
  • Substantial base of case studies with real-world applied AI
     

Predictive Maintenance:

  • We have developed PwC Smart Manufacturing Analytics Platform ‒ a set of analytic solutions to enhance the manufacturing process
  • Predict tool defects and machine downtimes before they happen to take proactive maintenance actions
  • Process production sensor data in real-time from machines to the global reliability portal
  • Analyze process steps, throughput time and its main drivers to derive process optimization measures
  • Increase product quality and reduce waste and costs by analyzing sensor data in the production process
  • Record, analyze and visualize position and movements of any resources in real time to improve shop floor and logistics efficiency
     

Geospatial Analysis:

  • Branch network analysis
  • Network planning and reformatting
  • Geo promotion analytics
  • Potential analysis
  • Client segmentation based on geospatial data
  • White spot analysis
  • Optimal location analytics
     

Pricing Strategy:

  • Development of promotion and pricing strategy
  • Develop pricing models, combining information from the client’s data-mart with external data to produce customer-specific price elasticity estimates
  • Construction of a decision support tool that recommended an optimal price point for each customer that maximized conversion rates along with expected future revenues
  • Recommendation of target customer lists for pre-approval campaigns by optimizing against
    margin and channel capacity constraints
     

Social Media Analytics:

  • Analysis of each customer previous purchases and social media activities help in preparation of personalized geotargeted offers in real time in shopping mall or at the airport
  • Sourcing Social Media sites such as Facebook, Twitter, LinkedIn
     

Risk Analytics:

  • Development of lifetime models for retail and corporate portfolios
  • Statistical modeling of macroeconomic impact
  • ECL/CECL impact study
  • Development of lifetime models (PD, LGD/EAD/EL)
  • ICAAP calculation
  • Stress testing
  • Provisioning optimization


Customer Analytics:

  • Behavioural Segmentation
  • Lifetime value calculation
  • Churn Management
  • Elastic Pricing
  • Loyalty Management
  • Digital Propensity
  • Cross/Up-sell improvement
  • Recommender systems (next best offer/next best action)
     

Churn Detection:

Our approach:

  • Churn prediction model (probability of occurrence, probability in time, the
    most probable factor causing churn), loss of customer value
  • Independent assessment of the anti-churn actions taken by the Organisation–
    comparing to market best practices, quantitative and qualitative analysis of churn
    phenomenon and identification of improvement areas
     


Meet Our Team

Behind every piece of data is a real human. Our team consists of Data Scientists, Data Engineers, Software Developers, BI Developers and more. Everyday we solve complex data challenges with natural curiosity, perseverance and focus.

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Contact us

Mariusz  Śpiewak

Mariusz Śpiewak

Managing Partner, Consulting, PwC Poland

Tel: +48 502 184 260

Jakub Borowiec

Jakub Borowiec

Partner, PwC Poland

Tel: +48 502 184 506

Kamil Kosiński

Kamil Kosiński

Senior Manager, PwC Poland

Tel: +48 519 504 021

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