OUR BUSINESS PILLARS

ANALYTICS ADVISORY


Specializing in bringing together subsystems to leverage data for competitive advantage

Business Pillars

Big Analytics Products and Platform

Data Science Advisory Services

Business Application Software Development

Business Focus

The Business Model Canvas

Strategies unique to represented products and platform 

Teaming for success with global partners 

Trusted advisor focus to solve client's business data challenges

Big Data Analytics Products and Platform

Solution Integration Smart Devices Big Data Consulting, training and support

Data Science Advisory Services 

Data Science Residency Data Exploratory Services Modeling and Visualization

Business Application Software Development

8 –12 Weeks Extreme Agile   Development

Products & Platforms

Data Acquisition & Integration

Data ETL & Mining

Data Cleaning, Preparation & Blending

Data Privacy and Security

Data Modeling

Deployment & Visualization

Big Data Repository

Real Time Big Data ingest and processing Platforms

Big Data Analytics Platform Applications

PRODUCTS

CUSTOMERS

ECONOMIC

OPERATIONS

Key Big Data And Data Security Partners 

 RoboInvestor allows non-quants or finance professionals to apply machine learning to their domain knowledge to aid their investment decision strategies. 

Enables non-quants or finance professionals without coding knowledge to apply machine’s ability to crunch large datasets and presents optimised results for backtest. 

Modular design allows customisation by adding specialised/proprietary market data , unique strategies and customised machine learning algorithms. 

Investment managers have full control on the models utilized and be able to input their domain knowledge for decision strategies. 

Using advanced machine learning techniques to derive insights from alternative data sets about events that may potentially drive the market. 

Data Science & Services

The 7 Steps of Machine Learning

  • Step 1 : Gathering Data

  • Step 2 : Prepare the Data

  • Step 3 : Choosing a model

  • Step 4 : Training

  • Step 5 : Evaluation

  • Step 6 : Parameters Tuning

  • Step 7 : Prediction 

Why Data Science Advisory

Understand Deeply

Frequent User Interactions

Focus on Business Needs

Feedback Driven Solutions ​

Deploy Fast

Start Simple

Increase Complexity if Needed

Improve Solutions Iteratively

Evaluate Constantly

Scale Big

Modular Design

Scale Quickly & Easily

Adaptable to Changes in Needs 

Visualize Meaning

Track Key Metrics

Minimal Technical Jargon    Intuitive Interpretations

Drive Actions

Software Development

Structure teams for Smart/Extreme Agile Development

Instead of lots of documentation nailing down what customer wants up front, our development methodology emphasizes plenty of feedback and collaboration with user by means of their control via catalog man days consumption

We embrace change, iterate often, design , code and test frequently ; keeping the customer involved and eliminate defects early , thus reducing overall costs.