The new versions of TextConverter, TARGET Data Processing Suite, and TARGET Application Development Suite have been released. Significant improvements, recently implemented by our development team, ensure even better performance, robustness, and ease of use than before. Here are release notes for release 4.9. All aspects of these enhancements will be explained in detail in coming tutorials.

Data extraction and mining have become more prominent processes within the average company’s IT department, especially as information volumes have soared and analytics solutions spread. When extraction and mining are not handled properly, other aspects of information governance and data management will almost certainly go awry.

Some of the more common sources of extra costs may be the tools and techniques used to extract and mine data. With this in mind, only the most powerful, efficient solution should be utilized at the time of project launches, and TextConverter has distinguished itself among other software solutions with respect to its incomparable speed, scope, accuracy and affordability.

This article describes the basic steps of configuring the SiMX TextConverter 4 data extraction project, outlining the following specific features:

> Tag based field extraction
> Multiple usage of a field tag
> Using field headers to name fields
> Multi-line fields
> Positional field extraction
> Multiple output tables
> Using script

November 18, 2016

FREMONT, CA - SiMX Corporation has been announced as one of the 2016’s top Data Integration provider among the list of 20 companies featured by CIOReview Magazine.

"It’s a great honor to select SiMX Corporation in our annual ranking list as one among the 20 Most Promising Data Integration Solution Providers 2016," said Jeevan George, Managing Editor of CIOReview.

Payroll reports are critical to track from several perspectives, including accounting, transparency, risk management, regulatory compliance and general financial oversight. Some of the more common tasks associated with payroll include the following: Data entry, Processing, Approvals, Reporting, Review. In the past, the vast majority of businesses had been handling these matters with paper filing systems. Although many have since begun to go paperless across their operations, plenty are still relying on this antiquated strategy to handle their payroll activities. This creates an unnecessary risk and inefficiency in the accounting department and beyond.

The accounts receivable department is responsible for overseeing, organizing and handling a tremendous amount of files and forms each year even when the company is not all that big. When the accounts receivable department begins to fall behind on invoices or simply does not have the tools necessary to complete its work, several issues can quickly come to pass.

The financial industry has been largely forced to be at the cutting edge of document and data management. From the rapid evolution of regulatory compliance requirements to market demands and beyond, information governance performances separate the winners from the losers in the financial industry. In addition to basic data management demands, the average financial industry contender needs to have advanced analytics capabilities to boot. Making major decisions without the insights of big data and other analytics solutions is already a risky proposition in this sector, especially considering the high adoption rates thus far.

Data extraction has become a far more critical aspect of healthcare management in the past several years, driven by the rapid influx of new technologies such as electronic medical record systems and enterprise mobility. Regulatory compliance has been intensifying in the sector, especially in the United States, and a vast portion of the total statutes being released are directly targeted at the progressive use of patient information for care improvement purposes. 

Data extraction and mining have become more prominent processes within the average company’s IT department, especially as information volumes have soared and analytics solutions spread. When extraction and mining are not handled properly, other aspects of information governance and data management will almost certainly go awry.

What’s more, some of the more common sources of extra costs may be the tools and techniques used to extract and mine data. This is why only the most powerful, efficient solution should be in play at the time of project launches, and TextConverter has risen to the top of the ladder with respect to speed, scope, accuracy and affordability.

Here is a short description of the most significant new features of the recently released TextConverter 4.5.

1. Full UNDO/REDO support.
2. Friendlier user interface.
3. Summary output.
4. Hidden output fields.
5. Automated mask generation for input and output filters.
6. Simplified input file navigation using page and line controls.
7. More precise control over positional output.
8. Data extraction from password secured Excel files.
9. Script control over all visual properties.

Data mining has had a marked impact on virtually every organization, regardless of size or industry, throughout the past several years. Globally, data volume growth has been unprecedented, with individual firms generating, collecting and storing more information than ever before. Much like a snowball effect, the digitization of operational processes has directly led to a constant acceleration in data proliferation.

Data automation software helps companies improve the reliability of their payroll practices. Each week or month, employees eagerly anticipate their paychecks in order to pay bills, loans and general living expenses. After long hard weeks at work, they look forward to the physical reward for their labor. When employees see their paychecks and feel that the figures are too small or that their vacation time or other factors are not accounted for, this is more than a hassle as it forges a foundation of distrust between employees and their employers.

Data automation software helps health care organizations save on various labor and operating costs. Health care providers rely on straightforward access to quality data to keep their operations running smoothly. Though health care entities might have extensive quantities of patient and employee data on various Excel, Word, PDF and other text files, employees can make mistakes. These problems range from simple data entry mistakes, to breakdowns in communication and poor documentation overall.

Human error is bound to occur in a workplace setting with large amounts of manual data entry. Avoid this problem through using data automation software today! Transcription errors are human data entry errors usually caused by typographical mistakes. These errors occur when employees are fatigued, not paying close attention, or accidently input the wrong figures or information. No matter what industry, data entry errors can cost organizations valuable time and resources rectifying mistakes with varying degrees of severity.