Business intelligence

Turn Your Raw Data into Deep Business Insight and Boost Your Profit with State-of-the-art Artificial Intelligence and Deep Learning. A Bargain That’s Too Good To Miss Out.

We all have learned that information means “meaningful data”. A classic example of information is end of year sales report. Such report provides information on how much was sold but not how each item sales affected, and was affected by other items. Such higher concept of knowledge, or Insight, cannot be obtained from static SQL quires for two main reasons:

  • The sheer amount of data, aka Big Data
  • The processing complexity of Big Data, which is simply infeasible for traditional SQL

Obtaining business insights is the job of Machine Learning. In contrast to static SQL queries, Machine Learning applies complex Data Mining algorithms such as Artificial Neural Networks and Random Forests to extract complex patterns and correlations hidden deeply in the data. Machine Learning can also predict future sales far more reliably than humans can.

If you are not already applying Business Intelligence, rest assured your competitors are!

At Infraflex, we understand that every customer’s requirements are unique, and that goes for their data as well. This implies that there is no universal solution to solve all problems. Instead, we build tailored solution to each problem using universal tools such as R, Python, Spark and H2O.

There is no limit to what Business Intelligence can offer to the retail industry. Examples:

  • Determining the optimum stock levels. This is critical to achieve customer satisfaction while avoiding the cost of over-stocking.
  • Deep understanding of customer purchasing habits to help deliver more relevant products to customers and boost customer loyalty.
  • Reveal hidden correlations between items sales to offer more relevant and personalised offers and promotions.
  • Optimise shelving (items placement) to boost sales of correlated items.

Traditionally, Financial institutions have relied on rule-based decision making systems to offer products to customers or detect frauds. Rule-based systems fail to address the needs of individual customers and often suffer from false negatives. BI offers significantly improved products and services.

  • Greatly improved real-time fraud detection with less false positives
  • Intelligent, pattern-based Anti-Money Laundering
  • Personalised products recommendation and limits such as loans per individual customer
  • Improved helpdesk service via intelligent smart agent

BI has proven to be an invaluable asset for schools and colleges of all kinds and sizes. The largest the school or college, the more crucial BI becomes. BI helps address various challenges in education, including:

  • Efficient allocation of assets such as classrooms, labs and other facilities
  • Smarter and optimised allocation of human resources
  • High quality service to students
  • Deeper insights into students’ performance
  • Accurate prediction of future trends

BI has proven to be critically vital to healthcare and it will continue to be so. BI allows healthcare centres to provide personalised service to patients in a way that is not possible with traditional means.

  • Truly personalised healthcare service to individual patients
  • Real-time prediction integrated into the workflow
  • Proactive admission and treatment
  • Early detection of cancer and other fatal diseases
  • Personalised medicine for individual patients needs

The construction industry has traditionally relied on personal experience to improve the accuracy of estimates of time, efforts and materials. Overestimation means unnecessarily high cost and underestimation results in delays and customer dissatisfaction. BI can do a lot to improve the industry by:

  • More accurate estimation of time, effort and material
  • Optimizing workflow to increase revenue and save cost
  • Avoiding potential risks and mitigating the impact when risks materialized
  • Faster Projects Delivery
  • Increasing customers’ satisfaction

Risk management importance can never be exaggerated for the insurance industry. Both in terms of prevention and mitigation. Traditional statistical methods are unable to cope up with changing factors. Failing to detect risks translate into direct financial loses and sometimes far worse.

BI can aid insurance companies in endless number of ways, including:

  • Estimating cost of goods and services
  • Customers’ risk and cost
  • Natural disasters detection
  • Political and social upheavals
  • Impact of global warming on business
  • Impact of pollution, etc.