RRP Solutions Business Intelligence Practice Ecosystem starts with Business Intelligence Reporting, where we understand the business and information architecture and offer the optimal solution, application and platform models to support your business.
Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information. The process of finding correlations or patterns among dozens of fields in large relational databases.Data mining consists of five major elements: Extract, transform, and load transaction data onto the data warehouse system. Store and manage the data in a multidimensional database system. Provide data access to business analysts and information technology professionals. Analyze the data by application software. Present the data in a useful format, such as a graph or table. Different levels of analysis are available: Artificial neural networks: Non-linear predictive models that learn through training and resemble biological neural networks in structure. Genetic algorithms: Optimization techniques that use processes such as genetic combination, mutation, and natural selection in a design based on the concepts of natural evolution. Decision trees: Tree-shaped structures that represent sets of decisions. These decisions generate rules for the classification of a dataset. Specific decision tree methods include Classification and Regression Trees (CART) and Chi Square Automatic Interaction Detection (CHAID) . CART and CHAID are decision tree techniques used for classification of a dataset. They provide a set of rules that you can apply to a new (unclassified) dataset to predict which records will have a given outcome. CART segments a dataset by creating 2-way splits while CHAID segments using chi square tests to create multi-way splits. CART typically requires less data preparation than CHAID. Nearest neighbor method: A technique that classifies each record in a dataset based on a combination of the classes of the k record(s) most similar to it in a historical dataset (where k 1). Sometimes called the k-nearest neighbor technique. Rule induction: The extraction of useful if-then rules from data based on statistical significance. Data visualization: The visual interpretation of complex relationships in multidimensional data. Graphics tools are used to illustrate data relationships.
Data Analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain. Data is extracted and categorized to identify and analyze behavioral data and patterns, and techniques vary according to organizational requirements.
Dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.
Here are the key characteristics of a dashboard:
All the visualizations fit on a single computer screen — scrolling to see more violates the definition of a dashboard. It shows the most important performance indicators / performance measures to be monitored. Interactivity such as filtering and drill-down can be used in a dashboard; however, those types of actions should not be required to see which performance indicators are under performing.
It is not designed exclusively for executives but rather should be used by the general workforce as effective dashboards are easy to understand and use.
The displayed data automatically updated without any assistance from the user. The frequency of the update will vary by organization and by purpose. The most effective dashboards have data updated at least on a daily basis.
A scorecard measures performance against goals. Typically, a scorecard displays graphic indicators that visually convey the overall success or failure of an organization in its efforts to achieve a particular goal. The scorecard is based on a collection of key performance indicators (KPIs), each of which represents an aspect of organizational performance. Taken together, these KPIs provide a snapshot of organization performance at a particular point in time.