science

Rexer's Annual Data Miner Survey

Rexer's Annual Data Miner Survey is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Rexer's Annual Data Miner Survey rather than just read about it. In short: Rexer Analytics’s Annual Data Miner Survey is the largest survey of data mining, data science, and analytics professionals in the industry. It consists of approximately 50 multiple choice and open-ended questions that cover seven general areas of data mining science and practice: (1) Field and goals, (2) Algorithms, (3) Models, (4) Tools (software packages used), (5) Technology, (6) Challenges, and (7) Future.

Key takeaways

Rexer's Annual Data Miner Survey belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Rexer's Annual Data Miner Survey to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Rexer's Annual Data Miner Survey from memory before moving on to harder problems.

Reference excerpt

Rexer Analytics’s Annual Data Miner Survey is the largest survey of data mining, data science, and analytics professionals in the industry. It consists of approximately 50 multiple choice and open-ended questions that cover seven general areas of data mining science and practice: (1) Field and goals, (2) Algorithms, (3) Models, (4) Tools (software packages used), (5) Technology, (6) Challenges, and (7) Future. It is conducted as a service (without corporate sponsorship) to the data mining community, and the results are usually announced at the PAW (Predictive Analytics World) conferences and shared via freely available summary reports. In the 2013 survey, 1259 data miners from 75 countries participated. After 2011, Rexer Analytics moved to a biannual schedule.

Surveys 2020 Survey: 579 participants from 71 countries. 2017 Survey: 1,123 participants from 91 countries. 2015 Survey: 1,220 participants from 72 countries. 2013 Survey: 68-item survey; 1,259 participants from 75 countries. 2011 Survey: 52-item survey; 1,319 participants from over 60 countries. Citations include: 2010 Survey: 50-item survey; 735 participants from 60 countries. Citations include: 2009 Survey: 40-item survey; 710 participants from 58 countries. Citations include: 2008 Survey: 34-item survey; 348 participants from 44 countries. Citations include: 2007 Survey: 27-item survey; 314 participants from 35 countries.

Recent survey results While the five Data Miner surveys have covered many data mining topics, the three topics that get the most attention in citations and at conference presentations are:

Algorithms: Each year the surveys have consistently shown that decision trees, regression, and cluster analysis form a triad of core algorithms for most data miners. However, a wide variety of algorithms are being used. This is consistent with independent polls of data miners conducted by KDnuggets over the years. Data Mining Tools: Data miners report using an average of four software tool to conduct their analyses. Over the survey years, R has risen in popularity. In 2010 it overtook SPSS Statistics and SAS to become the tool used by the most data miners. And the 2011 survey showed that R is now being used by close to half of all data miners (47%). STATISTICA has also grown in popularity. From 2007-2009 more data miners indicated that SPSS Clementine (now IBM SPSS Modeler) was their primary data mining tool than any other tool. However, in 2010 and 2011, STATISTICA was cited most frequently as data miners' primary tool. In terms of satisfaction with their tools, in the past few years, STATISTICA, SPSS Modeler, R, KNIME, RapidMiner and Salford Systems have received the strongest satisfaction ratings from data miners in these surveys. The growing popularity of R is consistent with independent polls of data miners conducted by KDnuggets, but the KDnuggets polls show a different picture regarding the popularity of commercial data mining software. Robert Muenchen has taken a multi-faceted approach to assessing the popularity of data analysis software - an approach that includes blog post counts, Google Scholar data, listserv subscribers, use in competitions, book publications, Google PageRank, and more. His analyses are consistent with the Rexer Analytics Surveys and KDnuggets in outlining the growth of R, but Muenchen illustrates that the popularity of software is more nuanced and one's conclusions will be different depending on what measure of popularity is used. The Rexer Analytics survey summary reports include analyses of the data miners' satisfaction with 20 dimensions of their software. Haughton et al. and Nisbet have also produced reviews of data mining software. Challenges: Consistently across the years, dirty data, explaining data mining to others, and difficult access to data are the top challenges data miners report facing. Participants in the 2010 survey shared best practices for overcoming these challenges.

References

External links Rexer Analytics home page Data Miner Survey Shows Positive Signs 2009 Decisionstats interview of Karl Rexer, President of Rexer Analytics The Popularity of Data Analysis Software Predictive Analytics World KDnuggets Polls: Many single-item polls of data miners conducted from 2000 to the present.

Worked examples

Example 1 — a first encounter with Rexer's Annual Data Miner Survey

Start with the simplest possible case. Write down what Rexer's Annual Data Miner Survey claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Rexer's Annual Data Miner Survey before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Rexer's Annual Data Miner Survey ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Rexer's Annual Data Miner Survey

In research: Rexer's Annual Data Miner Survey appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Rexer's Annual Data Miner Survey in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Rexer's Annual Data Miner Survey is common in secondary-school and first-year university syllabi. It links to neighbouring topics Data mining, Surveys (human research), so understanding it makes those chapters shorter.
In everyday life: Look for Rexer's Annual Data Miner Survey outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Rexer's Annual Data Miner Survey” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Rexer's Annual Data Miner Survey in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Rexer's Annual Data Miner Survey means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Rexer's Annual Data Miner Survey out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Rexer's Annual Data Miner Survey in simple terms?

Why does Rexer's Annual Data Miner Survey matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Rexer's Annual Data Miner Survey?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Rexer's Annual Data Miner Survey.