About
Welcome to our site. We specialize in Datamining for Internal Audit. What is datamining?
Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
It is related to data analytics
Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data.
Which is different from data analysis
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.
We will be making extensive use of the Python programming language. All our examples can be freely copied using the copy button. See an example below.
Code Example
from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification
X, y = make_classification(n_samples=1000, n_features=4,
clf = RandomForestClassifier(max_depth=2, random_state=0)
clf.fit(X, y)
print(clf.predict([[0, 0, 0, 0]]))Why Python? Python gives the flexibility to do exactly what you want. We will be using Python packages, which allready have the functionalities that we will need. Python gives us the ability to achieve exactly what we want, without being locked in a proprietary analytics software package. Also it gives us the apportunity to go deep “under the hood” so we can be confident the system behaves as we want it to behave. This results in more solid audit results, which can be communicated, as we can explain exactly how we came to certain conclusions.
It is no problem if you are not familiar yet with Python. We will provide a guided introduction. Also there are many great introductory “boot camps” to get to know Python quickly. This means there is a learning curve, but it will be greatly rewarding when you will be able to use Python to do some thoorough Audit Mining