The first stage involves understanding what the business would like to improve on or the problem it wants solved.
Relevant data needed to solve these business goals are decided upon by the business stakeholders and business users.
At this stage, key questions such as, “what data is available”, “how can we use it”, “do we have sufficient data” must be answered.
Explore the Data
This stage involves cleaning the data, making computations for missing data, removing outliers, and transforming combinations of variables to form new variables.
Time series graphs are plotted as they are able to indicate any patterns or outliers.
The analyst will plot the data using scatter plots (to identify possible correlation or non-linearity).
Analyze the Data
At this stage, using statistical analysis methods such as correlation analysis and hypothesis testing, the analyst will find all factors that are related to the target variable.
The analyst will also perform simple regression analysis to see whether simple predictions can be made.
It is at this stage that the data is cut, sliced and diced and different comparisons are made while trying to derive actionable insights from the data.
Predict what is likely to happen
At this stage, the analyst will model the data using predictive techniques that include decision trees, neural networks and logistic regression.
These techniques will uncover insights and patterns that highlight relationships and ‘hidden evidences’ of the most influential variables.
The analyst will then compare the predictive values with the actual values and compute the predictive errors.
Optimise (Best Solution)
We will find the best solution to meet your business goals and objectives.
We will apply the predictive model coefficients and outcomes to run ‘what-if’ scenarios, using targets set by managers to determine the best solution, with the given constraints and limitations.
The analyst will select the optimal solution and model based on the lowest error, management targets and his intuitive recognition of the model coefficients that are most aligned to the organisation’s strategic goal.
Harness your data. Discover opportunities. Elevate your insights.
Experience the power of data throughout your analytical journey. Stay in the flow of analysis, from data prep to analytics and collaboration. Answer questions you didn’t know you had. Share what you’ve discovered. Make data your most compelling partner in achieving your goals.nt continents, we have the expertise you’re looking for.
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WE WORKED FOR
The key members in data science and visualization team of Go Digital Lab, have previously worked at Mu Sigma and accordingly have the experience of working with Fortune 500 companies like Walmart, LinkedIn, Southwest Airlines to name a few.