2010 Rexer Analytics Data Mining Survey

Uli Bethke Best Practice, Business Intelligence, data mining, Training

The Rexer Analytics 4th Annual Rexer Analytics Data Miner Survey for 2010 is now available. 735 data miners participated in the 2010 survey. The main highlights of the survey are:

• FIELDS & GOALS: Data miners work in a diverse set of fields. CRM / Marketing has been the #1 field in each of the past four years. Fittingly, “improving the understanding of customers”, “retaining customers” and other CRM goals are also the goals identified by the most data miners surveyed.

• ALGORITHMS: Decision trees, regression, and cluster analysis continue to form a triad of core algorithms for most data miners. However, a wide variety of algorithms are being used. This year, for the first time, the survey asked about Ensemble Models, and 22% of data miners report using them.
A third of data miners currently use text mining and another third plan to in the future.

• MODELS: About one-third of data miners typically build final models with 10 or fewer variables, while about 28% generally construct models with more than 45 variables.

• TOOLS: After a steady rise across the past few years, the open source data mining software R overtook other tools to become the tool used by more data miners (43%) than any other. STATISTICA, which has also been climbing in the rankings, is selected as the primary data mining tool by the most data miners (18%). Data miners report using an average of 4.6 software tools overall. STATISTICA, IBM SPSS Modeler, and R received the strongest satisfaction ratings in both 2010 and 2009.

• TECHNOLOGY: Data Mining most often occurs on a desktop or laptop computer, and frequently the data is stored locally. Model scoring typically happens using the same software used to develop models. STATISTICA users are more likely than other tool users to deploy models using PMML.

• CHALLENGES: As in previous years, dirty data, explaining data mining to others, and difficult access to data are the top challenges data miners face. This year data miners also shared best practices for overcoming these challenges.

• FUTURE: Data miners are optimistic about continued growth in the number of projects they will be conducting, and growth in data mining adoption is the number one “future trend” identified. There is room to improve: only 13% of data miners rate their company’s analytic capabilities as “excellent” and only 8% rate their data quality as “very strong”.

You can request a copy of the full report by going to their data mining survey webpage

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.