Business Intelligence & Analytics

REALSOFT has focused on Augmented & advanced data analytics, data integration and data presentation since 1999

Overview

REALSOFT offers a comprehensive set of Business Intelligence & Analytics services to help clients harness structured data to improve decision-making, statistical analysis and customer services, REALSOFT solutions have powered many clients in the region with a comprehensive functionality e.g. Query and reporting, on-line analytical processing (OLAP), Dashboards, BI Platform, GIS analytics, , performance measurement technology( balance score cards, KPIs, analytics) using the most advanced technologies and best implementation practices.
Data analytics is the process of turning raw data into meaningful, actionable insights, then present these insights in the form of visualizations, such as graphs and charts, so that stakeholders can understand and act upon them

Descriptive Analytics

What happened? What is happening now?

The process of parsing historical data to better understand the changes that have occurred in a business. Using a range of historic data and benchmarking, decision-makers obtain a holistic view of performance and trends on which to base business strategy
Aims to answer the question “What happened?” (or What is happening?), characterized by traditional business intelligence (BI) and visualizations such as reports, pivot tables, and visualizations like histograms, line graphs, pie charts, and box and whisker plots
It involves parsing (or breaking down) data and summarizing its main features and characteristics. In this way, descriptive analytics presents what has happened in the past without exploring why or how.

Diagnostic Analytics

Why did it happen?  Why is it happening? What are the trends?  What patterns are there?

The process of using data to determine the causes of trends and correlations between variables. It can be viewed as a logical next step after using descriptive analytics to identify trends
It helps businesses delve into data to understand what’s driving trends and anomalies, such as an unexpected drop in revenue, a shift in customer behavior or an increase in expenses
Examines causes of trends to help companies better understand variations in performance and customer behavior. Employs data drilling, data mining and correlation analysis
Diagnostic analytics uses a variety of techniques to provide insights into the causes of trends. These include:
(*) Data drilling : Drilling down into a dataset can reveal more detailed information about which aspects of the data are driving the observed trends. For example, analysts may drill down into national sales data to determine whether specific regions, customers or retail channels are responsible for increased sales growth
(*)Data mining hunts through large volumes of data to find patterns and associations within the data. For example, data mining might reveal the most common factors associated with a rise in insurance claims. Data mining can be conducted manually or automatically with machine learning technology.
(*)Correlation analysis examines how strongly different variables are linked to each other. For example, sales of ice cream and refrigerated soda may soar on hot days

Predictive Analytics

What will happen? How will people react? Is this a fraud?

Looks at how trends might unfold in the future and their potential impact so that business leaders can take a more proactive, data-driven approach to decision-making
Predictive analytics uses statistics and modeling techniques to determine future performance
It is a form of technology that makes predictions about certain unknowns in the future
The most common predictive models include decision trees, regressions (linear and logistic), and neural networks, which is the emerging field of deep learning methods and technologies.

Prescriptive Analytics

What should I do? How can I make it happen?

Uses the results of descriptive, diagnostic and predictive analytics to suggest actions to respond to those future trends and improve business outcomes
Prescriptive analytics specifically factors information about possible situations or scenarios, available resources, past performance, and current performance, and suggests a course of action or strategy
It uses machine learning to help businesses decide a course of action based on a computer program’s predictions