The data mining software helps in proper representation of the figures collected to make a model or graph.
All the business strategies are based on the data collected over the time like past performances, past achievements, market trends etc. The data collected is of no use until it is organised in a form to relate the effect of one strategy to other and analyse the effect of each on the end result- sales.
Sometimes, with the use of software, those connections can be found which were unknown to us; like sales according to the season or sales according to the specific group of people residing in particular area. The data can be used for predictive analysis too, thus helping in taking important business decisions. Many business intelligence applications have in-built modules for data mining, but if you want to use best-of-breed software, those are also available.
We have put in great efforts in arranging the list of the best data mining software; you need to make the final decision of downloading one.
How to select the best data mining software?
The richness and usefulness of the data exploration feature
Data mining requires a very good understanding of data and that's why I consider this feature very important. Of course, there are software packages that are specifically built for this purpose and it is OK to use alongside with the DM package but it that would mean extra work and divided attention.
The data transformations that come with the package
All the DM packages provide data transformation facility but the difference is in the ease of use, their transparency as well as the option for implementing your own transformation.
Availability and versatility of machine learning methods
Some packages provide a rich set of methods and their variations to best suit the needs of the user while other make available just one version of a method. It not good or bad by itself and depends on the purpose.
Learning curve
Despite you or the staff to be using the package have a good level of data mining skills, each package comes with a set of specifics.
Existing experience with DM packages
If the team has experience with a DM software then choosing it or the similar one will be a good step as the learning curve will not be steep or non-existent.
Features:-
- Large quantities of data - The volume of data so great it has to be analyzed by automated techniques e.g. satellite information, credit card transactions etc.
- Noisy, incomplete data - Imprecise data is the characteristic of all data collection.
- Complex data structure - Conventional statistical analysis not possible
Benefits:-
- Predict future trends, customer purchase habits
- Help with decision making
- Improve company revenue and lower costs
- Market basket analysis
- Fraud detection