**4. Comparison of ConTra, Datax and WellGrowth apps**

Visual identification of inconsistencies in established patterns is achievable through data mining and analysis tools such as ConTra, Datax and WellGrowth apps. Each of these tools has its area of applicability depending on the kind of inconsistency explored. Datax for example, is most appropriately used for visualising patterns of missingness in CSV datasets unlike ConTra or WellGrowth that are used for mining and visualising contradictory data in patterns. **Table 3** presents a summary of the appropriateness of each of the tools in visualising inconsistencies in established patterns.


#### **Table 3.**

*Comparison of ConTra, Datax and WellGrowth apps.*

Six yardsticks were used in comparing the appropriateness of the explored tools and they include: pattern of missingness, amount of missingness, amount of contradiction, pattern of contradictory values, colour coding, and fault tolerance. ConTra and WellGrowth for example, does not mine missingness nor explore the pattern of missingness in a dataset. They do not measure the amount of missingness, unlike Datax that is designed to evaluate both the pattern and amount of missingness using Matrix Plot and bar charts respectively. It is evident from our discussions in this chapter, that ConTra and WellGrowth apps are used to explore inconsistencies notably contradictory data in established patterns of interest. In doing this, WellGrowth apps adopt colour coding and fault tolerance while Datax only adopts colour coding. **Table 3** depicts these discussed yardsticks for comparing ConTra, Datax, and WellGrowth apps.
