Follow the numbers
“Data isn’t about what you know; it’s about what you can discover.” — Pat Gelsinger
Follow the Numbers is a phrase commonly used in the context of data science and analytics. The phrase FOLLOW THE NUMBERS basically means, Making decisions, drawing conclusions, or uncovering insights based on the data and not relying on intuition or assumptions.
what does it mean by “follow the numbers” as a Data Scientist:
let’s dive in.
Data-Driven Decision Making:
As a Data Scientists you rely on data to make informed decisions. By analyzing the data sets, running statistical tests, to draw conclusions based on the evidence presented by the numbers.
Hypothesis Testing:
To answer a question or solve a problem, As a Data expert you will often formulate hypotheses and test it against the available data. By “following the numbers” you determine whether the data supports or refutes the hypotheses.
Pattern Recognition:
Uncovering patterns, trends, and correlations within a data set is a major role as a Data Scientist. You will use statistical and machine learning techniques to uncover valuable insights and make predictions.
Validation and Verification:
Following the numbers will also involve Validating your models and findings by comparing them to real-world outcomes or by cross-referencing with different data sources. This will ensures the accuracy and reliability of your analysis.
Data Visualization:
Communicating the findings, Scientists will use data visualization techniques to present the numbers in a visually compelling way. This helps you as well as the stakeholders to understand complex data and insights.
Iterative Process:
As a Data Scientist you continuously need to refine your models and analyses based on the new data and updated information, always “following the numbers” to guide their decisions.
Objective Decision Making:
“Follow the numbers” emphasizes the importance of objectivity in decision-making. As Data Scientists you aim to minimize biases and to always base your conclusions on empirical evidence rather than personal opinions.
Optimization:
In various applications like marketing, finance, and operations, as a Data expert using optimization techniques to find the best solutions based on numerical criteria, such as maximizing profits or minimizing costs.
Conclusion.
As a Data Scientist, you’re guided by the data you have at hand. You analyze, model, and make decisions based on the evidence presented by the numbers, ultimately striving for data-driven insights and solutions. This approach helps you and the organizations make well informed, efficient, and effective choices in various domains that have a data backing.
