Data Conversion
DFSTrans is a software tool able to perform everything from complex data conversion
and data transformation down to simple migration through a menu driven process with powerful metadata management
and embedded business logic. DFSTrans has wizards that simplify repetitive tasks. The project oriented menu system is
sufficiently flexible to handle very complex projects, yet is easy to use, easy
to maintain and drives the cost of data conversion down significantly when compared
to writing custom code. It is ideal for data managers who need
to do custom conversions for their clients on a regular basis.
Key Features Of DFSTrans
DFSTrans does what you’d expect any data conversion tool to do. What’s different is the level of project management control built into the menu driven process. Another powerful feature is it’s ability to perform dynamic queries based on the data found in your datasets. We’ve built in error handling for data mapping inconsistencies between different database types such as preserved words and column name conventions. If we haven’t thought of every function you might need, you can invoke custom function calls, then resume the process within DFSTrans. Next, DFSTrans lets you run each of your conversion scenarios separately in test mode and provides powerful debugging and auditing capability. For really big jobs, especially ones you may need to run repeatedly, you can tweak the performance of the process by configuring how DFSTrans handles paging
Instant/One Time specification of Data Conversion/Transformation/Migration.
Data integration among different systems from different vendors.
Simultaneous data manipulation and transformation among multiple data sources.
One to one, one to many, many to one data mapping capability.
Rich data manipulation functionality such as: Table joins, SQL query, Table merge/split, Row merge/split, Field merge/split, decision tree, and complex math formulas without programming, and when needed, you can use custom functions.
Powerful Dynamic Query (query filter based on dynamic data retrieved from data source at runtime)
Data validation and custom formatting (including custom function calls).
Handles database preserved words, column name spaces, table owner/schema names,
and various data types.
Powerful, multilevel project design, scenario control, testing and management capabilities.
Conversion process debugging, monitoring, and auditing capability.
Able to handle large data sets allowing tight control of memory paging requirements
for performance management.
Evaluation Guide and User Menu Guide to help you learn the system.
Typical Application Of DFSTrans
DFSTrans is designed for data managers who need to do complex data conversions quickly and as inexpensively as possible. Data conversion is often a costly afterthought, driving application development or solutions migration projects off schedule and over budget. There are lots of tools available, but most are simply not designed to do complex conversions of large data sets, or cannot handle integration and transformations of several databases simultaneously…certainly not for under $500. DFSTrans can do all the following
Migration of data from one database to another database. DFSTrans supports SQL Server, Oracle, Sybase, MySQL, Access, and other relational databases.
Merging several (varied or similar) databases into one database.
Migration of data from one database to multiple databases.
Importing flat file data into databases.
Exporting database data to flat files.
Transforming data among different databases.
Data integration among different data sources (database, flat files … etc.).
Extraction of filtered data in preparation for analysis, data mining or reporting.
Preparation of test data for software development team and QA team with subsequent clearing of test data.
DFSTrans Main Components
Data Source Connection Setup. Configures connections (via wizard or manually) for different data sources.
Schema Definition. Creates data table schema of data sources.
Logical Database Builder. Provides data filtering, table joining and field selection options in data preparation stage before transformation/conversion/migration takes place.
Data Conversion Builder. Design data conversion scenarios; specify data mapping rules; define data transformation rules; execute, debug and monitor the transforming process.
Data Transformation Process:
Step 1. Read data to scenario tables. Data tables retrieve data from data sources directly or through logical database object (SQL query).
Step 2. Execute scenario method. Apply transform rule during the conversion process.
Step 3. Write data into target source.
If you need help doing your data conversion, we also provide Data Conversion services using our DFSTrans technology – just give us a call.