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Big Data Analytics

The ability to store, aggregate, and combine huge amounts of data, and perform insightful analytics on the results, has finally become more accessible and cost-effective.

Xanadu’s Big Data framework is built around an understanding of business mechanics, analysis of the business strategy and identifying value in unstructured and structured data. We specialise in high performance, cost-effective data mining, predictive analysis and data processing using techniques from traditional AI and machine learning.

Our Process

    • Identify the current Business Model and its KPI’s.
    • Identify the Business Mechanics and the data that drives and represents the process.
    • Define and identify the 4 V’s – Volume, Variety, Velocity and Value in the context of the available data set.
    • Formalise a data management plan and data processing plan.
    • Refine Business Strategy based on the data analysis.

 

Data Tools Used

    • MapReduce/Big Query – Data processing framework
    • R, Python – Data Mining, Predictive Analysis
    • QlikView, Tableau, Pentaho – BI, Visualisation

 

Data Processing & Output Methods

    • Parallel computing, GPU processing
    • Date Warehousing – ETL, BI, Dashboards and KPI measurement
    • Visualisation

 

Data Analytics Methods

    • Data Mining - Regression, clustering and classification. We also leverage dimension reduction, collaborative filtering, association rules and standard information retrieval methods.
    • Predictive Analysis - Non-parametric regression and classification, Bayesian methods, time-series analysis, random forests, ensemble methods.
    • Decision Analysis - Decision trees, sensitivity analysis and simulation.
    • Optimisation - Integer and mixed-integer programming, stochastic and deterministic.