Data Analytics
Implement a process of mining, transforming and inspecting data to discover useful information and support decision-making. Engage Machine Learning for predictive modeling to identify business risks and opportunities, and enhance customer experience.
Analytics Solution Categories
Data Mining
Information collection, storage, archiving and lifecycle management
- Data Selection
- Cluster Analysis
- Machine Learning
- Regression Analysis
- Anomaly Detection
- Data Archiving
Stream Processing
Real-time data processing, aggregation, correlation and dissemination
- Data Streaming
- Data Aggregation
- Event Correlation
- Activity Monitoring
- Rules Enforcement
- Event Distribution
Business Reporting
Information pattern matching, predictive modeling and visualization
- Pattern Matching
- Historical Analysis
- Statistical Inference
- Scenario Simulation
- Results Evaluation
- Data Presentation
Analytics Solution Description
Data Mining
Information Collection and Statistical Analysis
In the era where competitive advantage requires fast time-to-market and instant reaction to customer feedback, collection of data from various related sources, and subsequent analysis of such data, help create high customer satisfaction and win in the marketplace. Modern Data Mining techniques allow discovering patterns in large data sets, involving methods at the intersection of Machine Learning, statistics and database management.
Our information architects will assist with the adoption of Big Data processing within your organization, creating a paradigm shift which is going to change the traditional approach to business intelligence. Our up-to-date experience with a spectrum of emerging open-source platforms leading the Data Analytics market allows us to position your company ahead of the curve with the data intelligence technology value stream.
Stream Processing
Real-time Information Aggregation and Distribution
The speed at which data is generated, consumed, processed and analyzed is increasing at an unbelievably rapid pace. Social Media and IoT markets are struggling to deal with the disproportionate size of data sets. These industries demand data analysis in real-time, where traditional Big Data tools no longer suffice.
We can develop a strategy and lead the implementation of open-source based solutions to deal with the streaming data — a never-ending sequence of records originating from more than one source. Such records can processed in memory and analyzed on the fly, with the ability to run ad-hoc queries on the stream state.
We will ensure that every open-source platform and tool is combined with an enterprise-level support, whether it be deployed on premise or operated out of a cloud-based Stream Processing environment.
Business Reporting
Business Intelligence and Data Presentation
Quite often, enterprises have a huge store of data that they have been accumulating for a long time, but they simply didn't know what to do with it. Big Data processing platforms and visualization tools allow to analyze and transform the data into actionable information that supports enterprise strategic and tactical business decisions.
Our information architects will guide your organization through the process of integrating business-critical data feeds into associative data processing environment, with Business Intelligence and online presentation capabilities that can quickly provide valuable insights. We will help you improve the quality of your data and discover deeper insights by combining key elements of data governance with interactive Data Analytics dashboards.
Analytics Standards
PFA
Portable Format for Analytics (PFA) is a JSON-based predictive model interchange format developed by the Data Mining Group (DMG). It is an emerging standard for statistical models and data transformation engines supporting Big Data processing.
Python
Python is an interpreted, general-purpose agile programming language and a platform managed by the Python Software Foundation (PSF). It is widely used within the Data Science community, for Statistical Modeling, Machine Learning and other analytical tasks.
Julia
Julia is a dynamic, general-purpose programming language and a platform designed for high-performance numerical analysis and computational science. It uses math-friendly syntax suitable for Artificial Intelligence and Scientific Computing.