The process of converting raw data into actionable insights is full of pitfalls which you, dear data bender, should be weary of. From the quality of data we use to how we communicate our findings, each step requires careful consideration.

Here are some of the most common data mistakes and how they can impact the reliability of our insights:

1. Poorly designed research questions

   Spare yourself the headache, come up with clear and concise research questions. Formulating vague or biased research questions will result in analyses that do not address the intended objectives.

   eg. "Do customers like our product? " is a vague question that does not define what aspect of the product satisfaction should be evaluated.

2. Insufficient or Wrong data

   Using incomplete or inaccurate data compromises the validity of the analysis results.

   eg. Drawing conclusions from an analysis that was based on half of the sample size that was required

3. Data Cleaning mistakes

   Failure to handle inconsistencies in the data like missing values or outliers messes with the the quality and reliability of the data. Missing values can significantly distort analyses, leading to incomplete insights. Ignoring or improperly addressing outliers, on the other hand, may result in skewed statistical measures, resulting to misinterpretation of the data. You should know when to drop missing data and when to impute it. While several imputation methods exist, the choice of which to apply depends on the end goal.

4. Improper analysis

   The first mistake is conducting analysis without knowing the data context, or using the wrong statistical methods.

   eg. Concluding that people preferred using cash over cards during a certain week without considering that PDQs were down that week. or Calculating the sum of age

5. Unclear communication of insights

   This ranges from incorrectly labeling your charts or using unclear visualizations making it difficult for anyone to grasp the key findings.

Avoiding these common mistakes is the key towards achieving accurate, actionable insights.

Happy Analyzing!!