Guest Post: Can Database Developers do Data Mining ?

Uli Bethke Best Practice, Business Intelligence, data mining, Data Warehouse, DW Design, ETL, Irish BI SIG, Oracle, SQL for Analysis, Training

I was recently invited by Sandro Saitta, who runs the Data Mining Research blog (, to write a guest blog post for him. The topic for this guest post was Can Database Developers do Data Mining ?

The original post is available at - Can Database Developers do Data Mining

Here is the main body of the post

Over the past 20 to 30 years Data Mining has been dominated by people with a background in Statistics. This is primarily due to the type of techniques employed in the various data mining tools. The purpose of this post is to highlight the possibility that database developers might be a more suitable type of person to have on a data mining project than someone with a statistics type background.

Lets take a look at the CRISP-DM lifecycle for data mining (Figure 1). Most people involved in data mining will be familiar with this life cycle.

Figure 1 – CRoss Industry Standard Process for Data Mining.

It is well documented that the first three steps in CRISP-DM can take up to 70% to 80% of the total project time. Why does it take so much time. Well the data miner has to start learning about the business in question, explore the data that exists, re-explore the business rules and understand etc. Then can they start the data preparation step.

Database developers within the organisation will have gathered a considerable amount of the required information because they would have been involved in developing the business applications. So a large saving in time can be achieved here as this will already have most of the business and data understanding. They are well equipped at querying the data, getting to the required data quicker. The database developers are also best equipped to perform the data preparation step.

If we skip onto the deployment step. Again the database developers will be required to implement/deploy the selected data mining model in the production environment.

The two remaining steps, Modelling and Evaluation, are perhaps the two steps that database developers are less suited too. But with a bit of training on Data Mining techniques and how to evaluate data mining models, they would be well able to complete the full data mining lifecycle.

If we take the stages of CRISP-DM that a database developer is best suited to, Business Understanding, Data Understanding, Data Preparation and Deployment, this would equate to approximately 80% to 85% of the total project. With a little bit of training and up skilling, database developers are the based kind of person to perform data mining within their organisation.

Brendan Tierney

About the author

Uli Bethke LinkedIn Profile

Uli has 18 years’ hands on experience as a consultant, architect, and manager in the data industry. He frequently speaks at conferences. Uli has architected and delivered data warehouses in Europe, North America, and South East Asia. He is a traveler between the worlds of traditional data warehousing and big data technologies.

Uli is a regular contributor to blogs and books, holds an Oracle ACE award, and chairs the the Hadoop User Group Ireland. He is also a co-founder and VP of the Irish chapter of DAMA, a non for profit global data management organization. He has co-founded the Irish Oracle Big Data User Group.