What are the basic problems Data Analyst have to work with?

Data analysts deal with six different categories of problems:

  1. Making predictions

  2. Categorizing things

  3. Spotting something unusual

  4. Theme identification

  5. Discovering connections

  6. Identifying patterns.

Making predictions

A corporation that wishes to know the most effective advertising approach for attracting new clients is an instance of a challenge that necessitates analysts making predictions.

Categorizing things

A company’s desire to enhance customer happiness is an instance of a challenge that requires analysts to categorize items. Analysts may use keywords or ratings to categorize customer calls.

Spotting something unusual

A firm that offers smartwatches that help individuals track their health could be interested in developing software that might detect unusual behavior. Analysts with experience analyzing aggregated health data may assist product developers in determining the best algorithms for detecting and triggering warnings when specific data does not trend as expected

Themes Identification

Analysts may be used by user experience (UX) designers to study user interaction data. Similar to challenges that involve analysts classifying items, usability improvement initiatives may require analysts to identify themes to assist in prioritizing the correct product elements for development.

Discovering connections

A third-party logistics company collaborating with another company to deliver items to clients on schedule is a problem that requires the identification of connections. Analysts can boost the number of on-time delivery by evaluating wait durations at shipping hubs.

Identifying patterns

Minimizing downtime due to machine failure is an example of an issue that requires analysts to search for patterns in data. For example, by reviewing maintenance data, they may determine that the majority of failures occur when normal maintenance is postponed for more than 15 days.