AT SIGMA DATA CHOPPER
Powerful Data Mining for Windows
|Do any of these questions sound
"How effective are our processes?"
"Are we producing at optimal yield?"
"How do we increase overall throughput?"
Well, Data Chopper will help you answer these questions and more...
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AT Sigma Data Chopper is a "Data Mining" tool which analyzes data stored in databases and attempts to discover relationships between variables represented by field names in the databases.
Its powerful logic allows it to
access virtually all popular formats such as Paradox, SQL tables
and other databases supported by Windows ODBC. This powerful
analysis tool makes it easy to analyze mountains of data and
detect relevant causative relationships.
AT Sigma Data Chopper "Drills Down" into data, evaluating causative relationships based upon specified criteria. Each mode attempts to discover relationships at progressive levels.
When using Data Chopper you will always know the top reasons for quality defects. This saves you time and money since you don't need to spend time searching for causes to problems. You can spend time correcting the problems.
Knowledge of relationship structures will help you refine your processes with a speed and accuracy that has never been possible before.
When you are looking for relationships in your data,
|Instead of looking
through all this:
just read this:
Get Data Chopper!
AT Sigma Data Chopper FAQ:
1) What is it?
AT Data Chopper is a data analysis tool.
2) What does it do?
AT Data Chopper ™ analyzes data stored in databases. AT Data Chopper attempts to discover relationships between variables. These variables are represented as field names in the databases.
3) What databases can be accessed?
Popular formats, particularly Borland Paradox databases, are accessed. The list includes SQL tables and other databases supported by Windows ODBC.
4) What database fields should be analyzed?
Typically, AT Data Chopper will use string and finite ordinal fields as Descriptive fields; AT Data Chopper will also select numeric fields these are classified as Measurement fields. Finite ordinal fields are fields that contain data that are generally from a set of commonly used fields that may be enumerated for storage purposes but represent another meaning. For example, a workday may be divided into shifts. These can be represented as shift 1, shift 2 and stored in the database as 1, 2 . Generally, ordinal fields are stored as integers.
5) What are Descriptive and Measurement fields?
Generally, Descriptive fields are database fields that represent the cause of the data produced or retrieved. Measurement fields, on the other hand, are the effects of the Descriptive fields. These definitions are the basis for the way AT Data Chopper works. For example, the operator of a machine in an assembly line is responsible for the quality of the parts produced. It is the operator's alertness, diligence, and attitude that can directly affect the quality. The actual specifications of the finished product are a result of the operator's work. Hence, for example, the uneven weight (a probable measurement field) of a product is a direct effect of an irresponsible operator ( a probable descriptive field ), the cause. The operator is the cause. AT Data Chopper is able to pinpoint which operator is most likely to produce defective parts.
6) What Descriptive/Numeric fields are selected?
By default, AT Data Chopper selects all available fields that satisfy the criteria of Descriptive and Numeric fields. The user can choose to select certain fields if preferred.
7) How does the user specify what records are analyzed?
The user can specify a date range and AT Data Chopper will only analyze those records that fall on or within the specified dates. AT Data Chopper will only permit a date range if the table contains a date field as part of the record's data. If however, a table does not contain a date field, then the user must process all records.
8) How detailed or accurate are the results?
AT Data Chopper operates in three modes. Each mode attempts to discover relationships at different levels. The accuracy of the results depend on the mode at which AT Data Chopper is used. Also, the results depend on the specifications provided for the variables examined.
9) What are specifications?
For AT Data Chopper to properly make data analyses, the user must provide specifications. These are ranges that define acceptable values for the variables examined. AT Data Chopper only examines Measurement fields. For these fields, the user must provide a range that describes the lowest acceptable value as well as the highest acceptable value. AT Data Chopper uses this range to classify the associated Descriptive fields. Each Measurement field used in the analysis must be provided a set of specifications.
10) What are the three modes that AT Data Chopper operates in?
AT Data Chopper uses Overall, Measurement, and Selective modes. Conceptually, the user should run the three processes in this order. By so doing, the user can pinpoint exactly what is sought.
11) What is analyzed in Overall mode?
In Overall mode, AT Data Chopper will inspect each record and verify that each measurement field satisfies the specifications provided for that particular field. Any record failing even one of the measurement field specifications will then be rejected and classified as defective. When multiple tables are analyzed, the table showing the highest defective percentage will be highlighted and brought to the user's attention.
12) What is analyzed in Measurement mode?
In Measurement mode, AT Data Chopper will inspect each record and verify if one particular measurement field's specifications are satisfied. AT Data Chopper inspects the entire table using only one measurement field. Then, the defective percentage is calculated. AT Data Chopper then proceeds to process the entire table again using the other measurement fields in succession. Defective percentages are then calculated and comparisons made among the different measurement fields. Using this mode, the user can infer which field produces the most defects and set out to analyze what is causing it.
13) What is analyzed in Selective mode?
In Selective mode, AT Data Chopper begins with the first selected Descriptive field. AT Data Chopper retrieves the contents of this field and matches this value with the first measurement field. Again, the measurement field is checked against the specifications for that field and the result noted. AT Data Chopper proceeds to the next measurement field using the same Descriptive value. The same happens here. When all measurement fields have been checked and associated with this one descriptive value, AT Data Chopper finds all records that contain this value as the Descriptive field.
When all records that contain this one Descriptive field have been found, AT Data Chopper proceeds to other unique values of the same Descriptive field. When done, AT Data Chopper iterates the entire process with the next selected Descriptive field. A defective percentage is then calculated for each unique value of each Descriptive field. From this, the user can scrutinize the results and determine which field adversely affects what field and take the necessary actions.
14) Does AT Data Chopper need a lot of time to configure and setup?
AT Data Chopper is able to make default selections. If specifications are available from a previous run, the user can simply select a table and AT Data Chopper will select all fields for processing. A future version of AT Data Chopper will also be able to infer specifications from the data presented. In short, all the user needs to do is select the tables and AT Data Chopper does the rest.