Such structures differ from the format used in table 2 , which shows the chemical constituents listed vertically in one column, repeating for each station.
The horizontal format allows the scientist to more conveniently view, compare, sort, and associate data that intuitively belong together. The tables may have hundreds of fields rather than be limited to a few tens of fields as in the vertical format, but the horizontal format obviously requires a fewer number of records. The horizontal table structure allows storage and use in both Excel and Access.
Even though they are related by a unique identification number and can be queried by DBMS software, some still refer to the tables as flat files because of the horizontal format, which is not normalized. Relational databases. Figure 1.
Example of database query. Figure 2. EMAP table relationships. Although the current database's total storage capacity is small in comparison with industrial or agency databases, it has many complex parameters and properties. The development and interactive use of the database throughout both the data processing and interpretative phases fig. Industrial managers now use "data mining" to perform statistical analysis and modeling techniques to uncover patterns and relationships hidden in an organization's database Edelstein, This intelligent data querying and exploration of data resources helps to uncover new relationships rather than merely to provide answers to standard queries, as traditional databases have done.
In a relational database this is easily enforced using the concept of foreign keys to ensure that customer IDs are filled in while creating an account, and also that said customer IDs already exist in another table. This is not possible with flat databases, which means that such a constraint has to be enforced by other means, such a through application code logic. Another limitation of flat databases vis-a-vis relational databases is the former's lack of query and indexing capability.
SQL queries cannot be written in flat databases because the data is not relational, and indexes cannot be created because the data is all lumped together in one table. Data in a flat database is typically only readable by and useful to the software application associated with the database. Flat databases are, or should only be, created for small, simple databases that will never grow large enough for the limitations outlined above to really become a problem.
Some real-life examples of flat databases are contact lists in a mobile phone and the storage of a high-scores list in a simple video game. In such cases, there would be little point and no justifiable expense in integrating a complex relational database engine into the computing platform because a simple flat database will do nicely.
By: Brad Rudisail Contributor. By: Kaushik Pal Contributor. By: Leah Zitter Contributor. Dictionary Dictionary Term of the Day. The file can be written by:. These simple tools can be used for tables with several thousand rows, corresponding to e. A flat file can easily be converted back and forth - to be formatted for any of the abovementioned simple tools, or for database software. The text file is typically a simple sequential text file. This means it will not allow modifications inside the file without a complete rewrite, and new data may only be added by appending at de end.
Although the file is intended for sequential access, direct access for reading will often be possible in certain cases:. Handwritten tables on paper sheets may be regarded as the first flat file databases, but the first machine readable ones were stacks of punched cards, introduced for the US Census.
Such a card has 80 hole columns for an 80 character text line. This was suitable for describing a US citizen, and processing the database implied putting stacks of cards into machines which sorted and counted cards on the basis of the values in specified columns.
In the sixties, text processing was done by punching each text line on a card, and 80 column text was for a while the standard for text processing, as well as for the text tables which had now become real flat file databases for computer analysis.
When data were stored on disks, it was common to store them as 80 column card images text lines , and the computer file database was born. In the eighties and nineties, flat file database programs were popular among computer users. But in the 21st century, computer users are likely to have and to know spreadsheet programs which are well suited for most flat file database operations.
The main advantage of the "real" database system is the ability for interlinking several tables into a complex model, as well as to display and analyze such interlinked structures.
The table format is now appropriate for database technology, but database technology will usually be of little interest in research because:. The data are often unsuitable for database analysis, even though the table shape seems right.
This can be explained for two very different types of research data. This is commonly done in geophysics , where a few variables are measured with fixed time intervals through perhaps a long period.
The little observation vector has no identifier which could be used as a database access key, as the position in the series is regarded as a valid identifier. This disqualifies this file from standard database processing. When questionnaire responses are gathered, very many variables are measured. In psychological research, when subjects may answer questionnaires repeatedly, and the questionnaire response variables may be duplicated in transformed versions, there may be hundreds of variables.
In such investigations, a separate flat file database will be needed for describing the variables, and a record describing a variable such as a questionnaire question, must be long enough to contain the question text, and also describe transformations done on the original variable.
But when this list of texts has been prepared, data files conforming to this setup can be collected repeatedly as simple flat files. A database system assuming a programmer-configured set of variables with simple names, will be unsuitable for dealing with a vector of long names.
The standard structure of a research data record for case data not time series data is: A text field identifying the case, followed by a floating point observation vector.
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