Challenge: Process a vast amount of structured and unstructured data. Analyse users' clusters and behavioural patterns using transactional, demographic and social media data.

• Visualise and segment millions of customers
• Increase customer loyalty developing new strategies using different data sources and identifying preferences of each subgroup
• Improve profit per customer by using mobile app statistics and target promotion campaigns

Challenge: Capitalise on internal and external long tail data

• Identify anomalies in transactional history
• Perform segmentation of transactional time-series and provided a key identifiers for each segment
• Refine parameters for risk management systems and visualise current classification model
• Analyse customer relationship data and provided detailed reports on customer segmentation

Challenge: Combine an extremely large amount of data from sensors, production lines and equipment performances.

• Optimise performance by visualising related faults and identifying root causes
• Mine manufacturing process data and determine a subset of the most influential predictors
• Boost performance and efficiency by identifying anomalies and choosing the most optimal third party company

Challenge: Investigate data sets include call logs, texts, device and location tracking, on-line activity and IP addresses.

• Increasing ARPU (Average Revenue Per User) and optimises upsell and cross-sell offers. Segment and visualise activity feeds to determine characteristics of the most valuable customers
• Optimise business operations in competitive environment by identifying outliers and inefficient activities

Challenge: Process a staggering amount of data by combining MWD (Measurement while drilling) and LWD (Logging while drilling) sensors data.

• Optimise mechanical performance by finding correlations between sensors data, predict system downtimes
• Quickly response to mechanical failures and unexpected obstacles by understanding the root cause
• Enable optimal drilling or completion decisions by evaluating high quality formation data

Challenge: Merge social and demographic data with users’ activity to understand hidden patterns and correlations. Mine natural language and perform sentiment analysis.

• Perform natural language analysis and identify different user groups
• Advance in image analysis and segmentation
• Identify hidden user patterns and target them
• Optimise conversion rates by understanding common parameters of lost customers