Analytics & Process
We follow a structured method enhanced by capability building of both people and technology.
Clarity of Purpose
Every engagement is focused on determining what will have the biggest impact on an organization.
Insights to Capability
We uncover robust new insights and then help our clients build capabilities to achieve continuous improvements.
Human + Machine
What we can measure and analyse, we can understand and change. We strive for clear analysis and insights from our cutting-edge technology.
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Address the Business Problems
Initially, business problems need to be addressed, the purpose of applying analytics is sometimes designated categorically or broken into parts. So, relevant data is selected to address these business problems by business users or business analysts equipped with domain knowledge.
Decision Making and Estimate conclusions
Analysts then would make decisions and endure action based on the conclusions derived from the model in accordance with the predefined business problems. Spam of period is accounted for the estimation of conclusion, all the favorable and opponent consequences are measured in this duration to satisfy the business needs.
Identify Potential Interest from Data
All sources of data having potential interest are required to identify. The key asset in this step is the more the data, the better it is. All the data will then be accumulated and consolidated in a data warehouse or data mart or at a spreadsheet file. Some exploratory data analysis is executed to do the computation for missing data, removing outliers, and transforming variables.
Interpretation and Evaluation by Experts
Finally, after obtaining model results, business experts interpret and evaluate them. Results may be clusters, rules, relations, or trends known as analytical models derived from applying analytics. Experts use predictive techniques like decision trees, neural networks, logistics regression to reveal the patterns and insights that show the relationship and invisible indication of the most persuasive variables.
Optimization of Best Possible Solution
Once the analytical model has been validated and approved, the analyst will apply predictive model coefficients and conclusions to drive “what-if” conditions, using the defined to optimize the best solution within the given limitations and constraints. Necessary considerations are how to serve model output in a user-friendly way, how to integrate it, how to confirm the monitoring of the analytical model accurately. An optimal solution is chosen based on the lowest error, management objectives, and identification of model coefficients that are associated with the company’s goals.
Inspect the data
Once moving to the analytics step, an analytical model will be predicted on the prepared and transformed data using statistical analysis techniques like correlation analysis and hypothesis testing. The analyst figures out all parameters in connection with the target variable. The business expert also performs regression analysis to make simple predictions depending upon the business objective. In this step, data is also often reduced, divided, crumbled and compared with various groups to derive powerful insights from data.