Meta S. Brown

Meta S. Brown helps organizations use practical data analysis to solve everyday business problems. A hands-on data miner who has tackled projects with up to $900 million at stake, she is a recognized expert in cutting-edge business analytics.

Articles & Books From Meta S. Brown

Cheat Sheet / Updated 02-17-2022
Data mining is the way that ordinary businesspeople use a range of data analysis techniques to uncover useful information from data and put that information into practical use. Data miners don’t fuss over theory and assumptions. They validate their discoveries by testing. And they understand that things change, so when the discovery that worked like a charm yesterday doesn’t hold up today, they adapt.
Step by Step / Updated 03-27-2016
University of Waikato faculty members develop tools as part of their work toward advancement of the field of machine learning. These tools are used in teaching, by scientists, and in industry. Weka is its general-purpose data-mining tool that offers a visual programming interface and a wide range of analytics capabilities.
Step by Step / Updated 03-27-2016
Using codes for data reduces data entry time, prevents errors, and reduces the memory requirements for storing the data. But the codes aren’t meaningful unless you have documentation, or labels, to explain their meaning. Some data formats enable you to enjoy the advantages of using codes while keeping the information about the meaning of the codes in the same file.
Step by Step / Updated 03-27-2016
Data miners work fast. One way to improve your productivity is to take full advantage of tools that let you do several things at once. It’s time-consuming (and boring) to set up a number of graphs separately, one at a time. So use these alternatives whenever you can:Data summariesTools that let you quickly ask for summaries of many variables, and get the summaries all at once.
Step by Step / Updated 03-27-2016
Because data miners lean heavily on basic graphs, some data-mining applications offer little or nothing more. Others provide a wide range of graph options, from the common to the exotic. It’s not necessary to use all of these, but you may benefit by selecting and using a few that suit your own needs. Data miners often use these graphs:Boxplot (also called box and whiskers)Histograms describe distributions of continuous variables, but have limited value for showing details.
Step by Step / Updated 03-27-2016
Your first hands-on step with data is getting it from wherever it is to the place where you need it to be. Text formats are common, and you’re likely to encounter them often. One of the most common is comma-separated value (.csv) text. KNIME.com AG is a small software and services firm focused on data mining. It offers a data-mining product with a visual programming interface.
Step by Step / Updated 03-27-2016
RapidMiner is a small software and services firm focused on data mining. It offers a data-mining product with a visual programming interface. To open the sample data in RapidMiner, follow these steps:Start RapidMiner Studio.RapidMiner is an offshoot of the YALE development project of the Dortmund University of Technology (Germany).
Step by Step / Updated 03-27-2016
The Bioinformatics Laboratory of the Faculty of Computer and Information Science, University of Ljubljana, Slovenia, develops Orange in cooperation with an open source community. To open the sample data in Orange, follow these steps:Start Orange Canvas.University of Ljubljana does not offer support agreements.
Article / Updated 03-26-2016
Data privacy is a big issue for data miners. News reports outlining the level of personal data in the hands of the US government's National Security Agency and breaches of commercial data sources have raised public awareness and concern. A central concept in data privacy is personally identifiable information (PII), or any data that can be traced to the individual person it describes.
Article / Updated 03-26-2016
Data collected by large organizations in the course of everyday business is usually stored in databases. But database administrators may not be willing to allow data miners direct access to these data sources, and direct access may not be the best option from your point of view either. Direct access to operational (used for routine business operations) databases can be a bad idea because Data miners use a lot of data.