CRISP DM process

Six Steps in CRISP-DM – The Standard Data Mining Process
Read the full story why CRISP-DM has become the standard data mining process?
Bonus: Unlock the new ways of Data Mining in just 6 easy steps!

Understanding your business objectives

Understanding About The Business (Step 1)
The initial stage of your CRISP-DM process involves a clear understating of what you want to accomplish from your business. It is necessary to know the key factors, that may have an influence on the outcome of your project.

CRISP-DM Data Understanding

Understanding the data (Step 2)
In this post, you will come to know about Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. Here, we have presented the crisp dm data understanding process, after the previous post on Phase 1 on Business Understanding.

CRISP DM Data Preparation Phase

Preparation of data (Step 3)
In this post, you will come to know about the crisp dm Data Preparation Phase(Cross Industry Standard Process for Data Mining), the third stage in the data mining process. In the previous phase, we had presented Data Understanding.

crisp dm modeling phase

Modeling (Step 4)
In this post, you will come to know about the crisp dm modelling phase (Cross Industry Standard Process for Data Mining), after the third post on Data Preparation.

CRISP-DM Evaluation Phase

Evaluation (Step 5)
Having learned about modelling in the previous post, in this post, you will get closely acquainted with CRISP-DM methodology. This is the fifth phase of data mining project, and this is all about evaluation.

crisp dm deployment phase

Deployment – Step 6 of the CRISP-Data Mining (DM) Process
In the last post we explained about evaluation phase of CRISP-DM, now we can discuss deployment phase of the crisp dm process, in this phase, you will come to know about the tactics to deploy results of your evaluation.

data cleansing techniques

Data cleansing techniques-How to delete unwanted data
Ever thought why your campaigns are not giving the desired results? Well you may find the answer inside! Click to read!

data entry outsourcing benefits for businesses

How outsourcing data entry helps business organizations?
From being cumbersome to the best and easy conversion, outsourcing data entry has multiple benefits. Read to find out.

What is Data Mining and Why is it so Important?
The process of data mining is used to detect abnormalities or inconsistencies, patterns, and correlations within data sets to anticipate outcomes.

data scrubbing

Data Scrubbing – How to Keep Your Data Clean and Accurate
Keep your information accurate, up to date and perfect. How? Data Scrubbing is the answer!
Read how with Data Scrubbing you can reach closer to 100% Data Accuracy.

data cleaning benefits

Data Cleaning Benefits, Definition, Process Explained – PGBS
Want to create a culture around quality data decision-making? You should take a vital data cleaning step, also referred to as data cleansing. Read More.