Report written by Marina Ghazaryan.
Data-driven decision-making is the process of making organizational and strategic decisions based on actual objective data instead of on intuition or observations. Today, every company in every industry aims to minimize the likelihood of business decisions going awry. Data is usually the answer.
Before making inferences from the available data, it is important to go through the process of identifying and amassing core information about the company’s industry, its competitive landscape, and its customers. Simply put, the more a company knows, the more accurate the decision can be.
It is also important to compile and coordinate all data sources. Data analysts typically perform their work following the ‘80/20 rule’, which means that they spend 80 percent of their time cleaning and organizing data, and the remaining 20 percent performing the actual analyses. Having clean and orderly information is essential. Generally speaking, data cleaning is the process of preparing raw data for analysis by removing data that is incorrect, incomplete, or irrelevant.
The next step after cleaning the data is analyzing the information using various statistical models. Here, the data analyst can start to build models to test the available data and attempt to find initial answers to the business questions identified earlier in the process. Testing the different models (linear regressions, decision trees, random forest modeling, and so on) can help the analyst to determine which method is best suited to the data set. It is also important to decide on the best way to present the information, ideally in an effective, and often visual, way.
Data analysts use these three common ways to present the information:
And finally, the cycle comes to an end with a conclusion stage, which is aimed at supporting the stakeholders throughout their deliberation and decision-making process. The more the findings are presented in an understandable manner the better the chances of successfully propelling the company’s strategy onward.
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