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The following is a list of just a few of the Pervasive DataTools features that are designed to make your data project as easy as possible. Each of these features, and many others, is described in detail in the Online Help that can be found in each product and in the Support area of this Pervasive DataTools website. For a look into the user interfaces of the various data tools, visit the Screenshots page.
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Loaders | Builders | Extractors | Parsers | Joiner | Investigators | Viewers
The following are some of the features available to you in the UpLoaders and DownLoaders.
The External Viewers (Source and Target) are available for you to view data in its native application, or with any other application that will read and display the data. You can view more than just the source/target file to which you are currently connected in the Data Loaders. Using the External Data Viewer, you can select your own viewer application, such as Notepad or any text editor to view ASCII text files, Microsoft Excel or OpenOffice Calc to view spreadsheets, and many others.
Error and event logging options in the Loaders are almost limitless. Basic logging options can be configured in the Preferences window. Advanced logging options are controlled and configured through the use of the advanced event handlers, event actions, and RIFL (Rapid Integration Flow Language).
The Loaders include a very powerful reject file/log file subsystem that you can use during the data transformation process. The reject records function allows you to create two files when you run a transformation. The target file/table contains the target data records and the reject file/table contains the records that are rejected, based on your criteria. So, the reject file will always be a subset of the source records.
There are five methods of doing “lookups” in a transformation: inline, static flat file, SQL Pass-through, dynamic SQL, and incore table. Each method is described in the documentation and has been rated on the following attributes: ease of use, portability, dynamism, and performance. Select the type of lookup that fits your specific needs.
There are several methods of sorting data as it is migrated from the source file/table to the target. Each method of sorting works best in specific circumstances. See the product documentation for details about each method.
The Loaders provide multiple methods of filtering data records. Different methods of filtering work best for specific circumstances. See the product documentation for details about each method.
Defining the Output Mode determines how data is written to your target file. The following output options are available in the Loaders: Replace File/Table, Append File/Table, Clear and Append File/Table, Delete File/Table, and Multimode. Some connections do not offer all of these options because the format, database, or application does not support it.
To assist you with the task of mapping source fields to your target file/table, the Loaders include a field mapping wizard, along with other helpful user interface clues. This wizard is particularly helpful where you have a single record type for both the source and the target AND have a non-multimode type of target connection. See product documentation for details about this feature.
View screenshots of the Data UpLoaders.
View screenshots of the Data DownLoaders.
The Data Builders include most the same features in the Data Loaders, and more...
All Data Builders read data from dozens of sources, allowing you to map data from virtually any database, application, or file format, and into a data file that can be imported into the specific target application.
Each Data Builder targets a specific application - some inside your firewall and others outside your firewall. Many are hosted applications that offer a hosted import utility. The purpose of each Data Builder is to help you create the "perfect file to import" into the target application, thus ensuring that clean data is imported into your application.
Each Data Builder includes one or more pre-built target schemas - depending on the application - complete with a description of each target field, built-in mapping rules, and visual clues to help you know how to map your data. The "store page" for each Builder lists the supported schemas for that target application.
The built-in mapping rules monitor the data as it is converted from the source to the target file. When the data violates a mapping rule, the source record is written to a "reject file", rather than to the primary target file.
Along with the automatically rejected records, any time a record is rejected, a message is written to the error and event log file that describes which mapping rule was violated for that specific record. This allows you to analyze, clean, or elect not to map those records to your target application.
View screenshots of the Data Builders.
Here are a few of the features of the Data Extractors...
The Data Extractors read data from a wide variety of text file report formats, including columnar, tagged, fixed, variable, hierarchical, and many others.
Your report file opens in a visual interface where you use your mouse to highlight anything from a single character to an entire block of data in your report. Then right-click to open menus with all the options you need to create definitions (rules) that extract the data you want.
Behind the visual interface and menus is a powerful extraction language with an almost unlimited capability of defining the rules for extracting data from even the most complex of report formats. Extraction rules can be defined by character patterns, line position, complex masking, and combinations of these using "AND/OR" logic.
While defining the data extraction rules, use the visual debugging window inside the Data Extractor to verify that the rules identify the correct lines of data in your report.
Along with the debugging feature, the Extractor includes a data browser where you can view the extracted data in a tabular (row and column) format. You can scroll through every extracted data record to verify you have extracted the data exactly as needed before exporting it.
When you are satisfied with the results of your data extraction rules, you can export the data to a CSV text file. The resulting CSV file can be imported into virtually any application, or you can use one of the other DataTools products (UpLoaders, DownLoaders, or Builders) to map, clean, and manipulate the data into your target database, application, or file format.
View screenshots of the Data Extractors.
The following are some of the features available to you in the Data Parsers.
Each Data Parser reads data from a specific file format commonly referred to as a "record manager". These types of source data files contain limited or no metadata, and are often accompanied by separate dictionary files that contain the metadata.
Each Data Parser includes two methods of parsing the data file into records and fields: 1) A visual parser in which you can manually define the structure of the records and fields, and 2) the ability to connect to and utilize a dictionary file to define the structure. Each method provides the metadata necessary to parse the data into a structured format that can be mapped to a more universal file format.
Along with the parsing features, the Parsers include a data browser where you can view the parsed data in a tabular (row and column) format. You can scroll through every source data record to verify you have parsed the data exactly as needed before exporting it.
When you are satisfied with the results of your data parsing, you can export the data to a CSV text file. The resulting CSV file can be imported into virtually any application, or you can use one of the other DataTools products (UpLoaders, DownLoaders, or Builders) to map, clean, and manipulate the data into your target database, application, or file format.
View screenshots of the Data Parsers.
Here are a few of the features of the Data Joiner...
The Pervasive Data Joiner enables virtually anyone to join data from multiple tables and files via a graphical interface and menu options. The sources can be multiple tables or views from one database or multiple heterogeneous sources.
When you need complex joins, the Data Joiner includes a graphical SQL query builder in which you can build - and save! - complex queries to join even more data.
After connecting to your sources, simply click to select a matching key field in each of the sources.
In the same graphical interface, click to select the data fields you want to include in the target data file.
The Data Joiner includes a data browser where you can view the data of each source and the joined in a tabular (row and column) format. You can scroll through every source data record in the file to verify that your join settings are correct before the data is exported to the target file.
When you are satisfied with the results of your join settings, you can export the data to a CSV text file. The resulting CSV file can be imported into virtually any application, or you can use one of the other DataTools products (UpLoaders, DownLoaders, or Builders) to map, clean, and manipulate the data into your target database, application, or file format.
View screenshots of the Data Joiner.
Coming soon
The following features are available to you in the Viewers.
The Data Viewers read data from dozens of sources, allowing you to view the data from virtually any database, application, or file format without the need to purchase the native application from which the file originated.
After connecting to the source, the Data Viewers include a data browser where you can view the data in a tabular (row and column) format. You can scroll through every source data record in the file. And the Browser includes a "search" function so you can find specific information contained within the file.
View screenshots of the Data Viewers.