Each of the links below will open a case study that describes how one of our community members used DataTools to solve a data migration and/or data conversion challenge. Most of the case studies include a description of both the "Problem" and the "DataTools Solution".

We hope these case studies help you understand how DataTools can work for you!

Customer Case Studies

Extract Data from Legacy Text Files

Recently we found ourselves having to audit specific employee historical data that resided in our old antiquated legacy HR/Payroll system. Because there was no real way of extracting the data from the actual database tables...

Creative Solutions Accounting to Microsoft Dynamics SL 7.0

Previously, we had a CPA firm doing our accounting using Creative Solutions Accounting software, and we needed to convert four years of data for two companies to Microsoft Dynamics SL 7.0 (Solomon) for a January 1, 2008, implementation...

You're Invited!

If you would like to write a case study for publication on this page, please use the contact form to send us a brief description of how you used DataTools to migrate or convert your data. If desired, your personal and company information will be kept confidential, and we will work with you to write an article that accurately describes your data project and your DataTools solution.

Do you need to load data into an eBay, Yahoo, Amazon.com, or GoogleBase web store?

Pervasive DataTools offers two ways to help you get clean, accurate data into these web stores quickly and easily! Here's how...

Pervasive Data Builders

With any of the eStore Data Builders you can migrate data from dozens of applications, databases, and file formats using native adapters to connect to your source data. Then map and manipulate that data into a CSV text file with the exact structure required by the web store's import utility.

A Data Builder is currently available for the following eStores: Amazon.com, eBay, and GoogleBase. We are also developing a Data Builder for Yahoo.

Pervasive Data UpLoaders

Using one of these Data UpLoaders, you can migrate data from dozens of applications, databases, and file formats to a clean data file that can be imported into virtually any web store.

Data UpLoader to CSV Text

Using the Data UpLoader to CSV Text, you can migrate data from dozens of applications, databases, and file formats to a CSV text file that can be imported into any web store where the import utility requires a CSV file.

Data UpLoader to Excel

Using the Data UpLoader to Excel, you can migrate data from dozens of applications, databases, and file formats to a Microsoft Excel file that can be imported into any web store where the import utility requires an Excel file.

The information here is designed to help you understand your data files and how Pervasive DataTools can help you convert virtually any data file. Here we will address types of data files, sources of data files, and how one or more of the DataTools products works with each.

Data File Types | Data File Sources

What Type of Data Files Do You Have?

There are many ways to classify data files: storage format, readability, structure, etc. In the tables below you will find brief explanations of some of the types of data files, and which of our DataTools products work with each.

Data Storage Formats

At the highest level of classification, data file storage formats can be grouped into two categories of formats. Each is described below.

Open vs. Proprietary Formats

Open Formats

Open file formats are common formats that can usually be exported from or imported into databases and applications.

While these files are somewhat "transportable", the quality of the data and schema differences between the data file and the database or application into which you need to import the data add complications. The data often must be cleaned and transformed prior to loading the data into your target.

Three of the most common open file formats are: CSV text, or tab delimited ASCII, and xBASE (.DBF) files.

Proprietary Formats

Most databases and applications store the data in their own proprietary format.

The Data Parser for Binary data enables you to do the following for binary data files:

• Define source record length
• Define source field sizes and data types
• Define source data properties
• Assign source field names
• Define schemas with multiple record types

How to Parse Your Source Data

The Data Parsers provide two methods by which you can parse your source data file, as follows:

Use a Dictionary File

If you have a dictionary file that contains the record schema, the Data Parser can read and apply the structure to your data file.

Two types of dictionary files are supported by the Data Parsers:

• External Dictionary Files - These are the most common dictionary files, and include COBOL copybooks, ASCII record structures, Btrieve DDFs, and others.
• Internal Dictionary - Only C-TREE+ by Faircom uses an internal dictionary where the record structure is stored inside the data file. The Data Parser for C-TREE supports their internal dictionary.

Define the Record Structure Manually

If you have a printed copy of the schema of your source data file, use the Data Parser to define the structure of your data records manually in the graphical interface. You may define record length, field lengths, and select from an exhaustive list of data types.

What to do with Your Parsed Data

After using any of the above methods of defining the record structure, the content of the now unpacked data records can be viewed in the built-in Data Browser and exported to a delimited ASCII CSV or unicode CSV text file, including support for double-byte, multibyte, UTF-8, UTF-16, and other international encodings.

The Data Parser for Binary data enables you to do the following for COBOL data files:

• Define source record length
• Define source field sizes and data types
• Define source data properties
• Assign source field names
• Define schemas with multiple record types

How to Parse Your Source Data

The Data Parsers provide two methods by which you can parse your source data file, as follows:

Use a Dictionary File

If you have a dictionary file that contains the record schema, the Data Parser can read and apply the structure to your data file.

Two types of dictionary files are supported by the Data Parsers:

• External Dictionary Files - These are the most common dictionary files, and include COBOL copybooks, ASCII record structures, Btrieve DDFs, and others.
• Internal Dictionary - Only C-TREE+ by Faircom uses an internal dictionary where the record structure is stored inside the data file. The Data Parser for C-TREE supports their internal dictionary.

Define the Record Structure Manually

If you have a printed copy of the schema of your source data file, use the Data Parser to define the structure of your data records manually in the graphical interface. You may define record length, field lengths, and select from an exhaustive list of data types.

What to do with Your Parsed Data

After using any of the above methods of defining the record structure, the content of the now unpacked data records can be viewed in the built-in Data Browser and exported to a delimited ASCII CSV or unicode CSV text file, including support for double-byte, multibyte, UTF-8, UTF-16, and other international encodings.

The Data Parser for Btrieve data enables you to do the following for Btrieve data files:

• Define source record length
• Define source field sizes and data types
• Define source data properties
• Assign source field names
• Define schemas with multiple record types

How to Parse Your Source Data

The Data Parsers provide two methods by which you can parse your source data file, as follows:

Use a Dictionary File

If you have a dictionary file that contains the record schema, the Data Parser can read and apply the structure to your data file.

Two types of dictionary files are supported by the Data Parsers:

• External Dictionary Files - These are the most common dictionary files, and include COBOL copybooks, ASCII record structures, Btrieve DDFs, and others.
• Internal Dictionary - Only C-TREE+ by Faircom uses an internal dictionary where the record structure is stored inside the data file. The Data Parser for C-TREE supports their internal dictionary.

Define the Record Structure Manually

If you have a printed copy of the schema of your source data file, use the Data Parser to define the structure of your data records manually in the graphical interface. You may define record length, field lengths, and select from an exhaustive list of data types.

What to do with Your Parsed Data

After using any of the above methods of defining the record structure, the content of the now unpacked data records can be viewed in the built-in Data Browser and exported to a delimited ASCII CSV or unicode CSV text file, including support for double-byte, multibyte, UTF-8, UTF-16, and other international encodings.

The Data Parser for C-ISAM data enables you to do the following for C-ISAM data files:

• Define source record length
• Define source field sizes and data types
• Define source data properties
• Assign source field names
• Define schemas with multiple record types

How to Parse Your Source Data

The Data Parsers provide two methods by which you can parse your source data file, as follows:

Use a Dictionary File

If you have a dictionary file that contains the record schema, the Data Parser can read and apply the structure to your data file.

Two types of dictionary files are supported by the Data Parsers:

• External Dictionary Files - These are the most common dictionary files, and include COBOL copybooks, ASCII record structures, Btrieve DDFs, and others.
• Internal Dictionary - Only C-TREE+ by Faircom uses an internal dictionary where the record structure is stored inside the data file. The Data Parser for C-TREE supports their internal dictionary.

Define the Record Structure Manually

If you have a printed copy of the schema of your source data file, use the Data Parser to define the structure of your data records manually in the graphical interface. You may define record length, field lengths, and select from an exhaustive list of data types.

What to do with Your Parsed Data

After using any of the above methods of defining the record structure, the content of the now unpacked data records can be viewed in the built-in Data Browser and exported to a delimited ASCII CSV or unicode CSV text file, including support for double-byte, multibyte, UTF-8, UTF-16, and other international encodings.

The Data Parser for C-TREE data enables you to do the following for C-TREE and C-TREE+ data files:

• Define source record length
• Define source field sizes and data types
• Define source data properties
• Assign source field names
• Define schemas with multiple record types

How to Parse Your Source Data

The Data Parsers provide two methods by which you can parse your source data file, as follows:

Use a Dictionary File

If you have a dictionary file that contains the record schema, the Data Parser can read and apply the structure to your data file.

Two types of dictionary files are supported by the Data Parsers:

• External Dictionary Files - These are the most common dictionary files, and include COBOL copybooks, ASCII record structures, Btrieve DDFs, and others.
• Internal Dictionary - Only C-TREE+ by Faircom uses an internal dictionary where the record structure is stored inside the data file. The Data Parser for C-TREE supports their internal dictionary.

Define the Record Structure Manually

If you have a printed copy of the schema of your source data file, use the Data Parser to define the structure of your data records manually in the graphical interface. You may define record length, field lengths, and select from an exhaustive list of data types.

What to do with Your Parsed Data

After using any of the above methods of defining the record structure, the content of the now unpacked data records can be viewed in the built-in Data Browser and exported to a delimited ASCII CSV or unicode CSV text file, including support for double-byte, multibyte, UTF-8, UTF-16, and other international encodings.

The Data Parser for Micro Focus COBOL data enables you to do the following for Micro Focus COBOL data files:

• Define source record length
• Define source field sizes and data types
• Define source data properties
• Assign source field names
• Define schemas with multiple record types

How to Parse Your Source Data

The Data Parsers provide two methods by which you can parse your source data file, as follows:

Use a Dictionary File

If you have a dictionary file that contains the record schema, the Data Parser can read and apply the structure to your data file.

Two types of dictionary files are supported by the Data Parsers:

• External Dictionary Files - These are the most common dictionary files, and include COBOL copybooks, ASCII record structures, Btrieve DDFs, and others.
• Internal Dictionary - Only C-TREE+ by Faircom uses an internal dictionary where the record structure is stored inside the data file. The Data Parser for C-TREE supports their internal dictionary.

Define the Record Structure Manually

If you have a printed copy of the schema of your source data file, use the Data Parser to define the structure of your data records manually in the graphical interface. You may define record length, field lengths, and select from an exhaustive list of data types.

What to do with Your Parsed Data

After using any of the above methods of defining the record structure, the content of the now unpacked data records can be viewed in the built-in Data Browser and exported to a delimited ASCII CSV or unicode CSV text file, including support for double-byte, multibyte, UTF-8, UTF-16, and other international encodings.

The Data Parser for Fixed Text data enables you to do the following for fixed length text and unicode text data files:

• Define source record length
• Define source field sizes and data types
• Define source data properties
• Assign source field names
• Define schemas with multiple record types

How to Parse Your Source Data

The Data Parsers provide two methods by which you can parse your source data file, as follows:

Use a Dictionary File

If you have a dictionary file that contains the record schema, the Data Parser can read and apply the structure to your data file.

Two types of dictionary files are supported by the Data Parsers:

• External Dictionary Files - These are the most common dictionary files, and include COBOL copybooks, ASCII record structures, Btrieve DDFs, and others.
• Internal Dictionary - Only C-TREE+ by Faircom uses an internal dictionary where the record structure is stored inside the data file. The Data Parser for C-TREE supports their internal dictionary.

Define the Record Structure Manually

If you have a printed copy of the schema of your source data file, use the Data Parser to define the structure of your data records manually in the graphical interface. You may define record length, field lengths, and select from an exhaustive list of data types.

What to do with Your Parsed Data

After using any of the above methods of defining the record structure, the content of the now unpacked data records can be viewed in the built-in Data Browser and exported to a delimited ASCII CSV text file or a delimited unicode CSV text file, including support for double-byte, multibyte, UTF-8, UTF-16, and other international encodings.