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Quantum-Web » Data Science and Advanced Quantitative Modeling

Data Science and Advanced Quantitative Modeling


Successful decision-making will increasingly be driven by analytics-generated insights. And the more accurate and timely these are, the better chance a (human or automated) decision-maker must anticipate and profit from change. The keys to effective data-driven decision-making are the ability to sift through large amounts of data; and the ability to combine data from several sources to gain a more comprehensive view of the business. Seemingly unimportant data can become crucial when combined with other sources to reveal new insights. For example, combining what people write in social media with network data can play a vital role in fully understanding the way users experience a service, or in knowing whether they are likely to churn.

Quantum-Web assists clients by transforming data into actionable Insight by:

  1. Data collection (structured, unconstructed or random data).
  2. Filtering and compression of irrelevant data.
  3. Analysis information with proprietary and models
  4. Forecasting algorithmic output through decision support system.
  5. Insight to facilitate business decisions from actionable insight.


Data collection (structured, unconstructed or random data)

Big data collection is a major activity among small to large business enterprises. Business intelligence is enhanced while marketing strategies are optimized with the help of the data collection process. There are varieties of ways by which we gather data for our analysis. Which data collection strategies will best fit will depend upon what types of technologies we are using and whether it is optimised in collecting the specific data we need for. The ability to collect data and use them to business advantage will also depend upon how we can interpret what the data means.


Filtering and compression of irrelevant data.

What value exists in your data? We help you set your data and analytics priorities by:

  • Evaluating the available data and its quality and what can – and can’t – do with it, to build a clear view of its potential business value.
  • Supporting data collection, preparation and cleansing, if needed.
  • Completing basic techniques to help identify data potential – including profiling, segmentation and benchmarking.

As customers purchase, consume and interact digitally and operational processes are tracked and monitored digitally. This data explosion has combined with technology change in low-cost cloud computing and storage capacity, enabling analytics that would previously have been technologically impossible or economically impractical.


Analysis information with proprietary and models

Our econometric, machine learning, and operations research techniques are deployed to assist our clients with data analytics. The main area of modeling includes:

  • Descriptive modeling
  • Predictive modeling
  • Prescriptive modeling

What is the right answer for your business? We help you discover the right answers for your business by evaluating the descriptive and predictive insights available and completing incremental analysis to find the optimal solution to your business problem, given your specific constraints and business priorities.


Forecasting algorithmic output through decision support system.

What might happen next? We help you use your data to anticipate and predict, to allow you to plan effectively, by:

  • Using data patterns from the past, combined with industry and company knowledge, to more accurately anticipate the future.
  • Building close to real-time predictive analytics solution – with new data constantly updating and improving predictive outcomes, designed to be automated and embedded into your business processes.
  • Helping to identify and predict very specific hidden activities – such as fraud and market manipulation if these are considered potential risks.


Insight to facilitate business decisions from actionable insight.

Is insight being delivered to the right people at the right time? We help you make sure that the right data and insight are being delivered to the right people at the right time, by

  • Working closely with you to understand the key people who need access to data and insight in order to drive and sustain business change.
  • Developing the most relevant visual and interactive outputs to meet the different business needs of these audiences – from ‘C’ suite dashboards to data ‘drill-down’ solutions for operational managers, to key customer insights delivered to the screens of call centre agents.
  • Advising on the integration of data analytics systems into the broader eco-system of your organisation, to automate the application of data insights in your day-to-day business processes.
  • Designing the integrated set of capabilities, you will need to become effective at data analytics – covering technology strategy, analytics and visualisation tools, process and operating model evolution, people and training needs.
  • Providing managed outsourced services – supplying on-going solutions to your organisation, encompassing data hosting, analytics, and business recommendation.