Improving Strategic Planning and importance of EDA

Data Science, AI and ML
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After data has been worked on and refined, EDA can be done on that data. It is used to perform investigations on data, find patterns, discover anomalies, use statistics to arrive at conclusions. Improvements in computation have led to developments in EDA.

Better resolution displays, sophisticated user interfaces, 4K displays have all made EDA a more pleasant experience. Gone are the days, when you had to plot a bar chart on graph paper. Now you can just share your Power BI dashboard across the team. Charts, graphs and data visuals provide valuable conclusions on how to proceed. Abundant data available these days can be applied and discoveries and insights can be obtained from the highly detailed data.

EDA is very valuable from the perspective of data science, to make certain that the results that are produced are valid and are applicable to the desired business contexts. EDA allows the systematical assessment of the contents of one data field and its interaction with other data fields, which is often the key metric representing behaviour or data the business wants to analyze or predict (eg. Customer age, customer spending, sale of a particular product in a particular area etc).

These methods help identify potential causes for behaviour, identify potentially problematic or spurious data points, and develop hypotheses to test that will shape their analysis and model development strategy.

Through EDA methods, assumptions are validated and patterns are identified, which helps in understanding the problem and model selection. This ensures high-quality analysis and validates that the data was generated the way it was expected to.

Improving Strategic Planning in organizations

Successful data mining and working with data will lead to efficient EDA, which will give better business strategies to companies, aiding in strategic management, efficient decision making, supply chain management and hence give the company a competitive advantage over others.

This will reflect in the net performance of the economically in terms of profits. Successful strategic planning in organizations aims at a desired future, goals or achieving the desired target. It is about taking a look at the wider picture and optimising the course of actions.

Armed with data, numbers, statistics, predictions and other insights, preparations are done from the aspect of Data Science. This undoubtedly gives an added advantage. Say for example, in a company if all parameters of the market and the sales of its products are predicted, they are able to aggregate their methods into one centralized corporate plan, organizational structure and a predefined budget. All this concludes into the efficient running of the company.