Q & A
Data Analysis

Q: What Are the Problems That a Data Analyst can Encounter While Performing Data Analysis?

What Are the Problems That a Data Analyst can Encounter While Performing Data Analysis

1. Data Quality Issues

  • Analysts trying to complete their analyses use data of varying quality; some of these issues could include poor coding, mislabelled values or empty fields.
  • Analysts will spend a considerable amount of time cleaning the data and trying to determine which of these data quality issues they will have to consider for further processes in data processing.
  • This data cleaning and processing can be both time-consuming and labour-intensive.

2. Data Accessibility

  • Analysts trying to gather information and/or conduct analyses will sometimes face challenges in obtaining the data they need.
  • Sometimes, the analyst does not have access to that data, or, in other cases, the analyst must wait for approval from another department or external entity to get access to the data. As a result, this may cause delays and prevent the analyst from completing his/her analysis on time.

3. Data Integration

  • When analysts combine two or more different datasets to complete a single analysis, this can result in problems with data integration.
  • In many situations, if there are discrepancies between the datasets, they will require an additional step in the data integration process to reconcile the discrepancies.
  • For data analysts to produce accurate analyses, it is essential that the data be as consistent as possible between all datasets utilized in the analysis.

4. Tool Limitations

  • The limitations of the tools and software that data analysts use can also create challenges when attempting to analyse data.
  • Analysts may experience performance issues relating to slow uploading or downloading of data files, may not have adequate software capabilities for the type of analysis needed, or may need advanced technical capabilities to perform their analyses.

5. Interpretative Issues

  • It is often difficult for data analysts to interpret complex data and draw valid conclusions.
  • Data interpretation challenges stem from a lack of understanding of the definitions of, and relationships between, data fields/columns, and from data preparation and analysis processes.