ASA – Alphanumeric String Analyzer is a tool that work in internet intranet and help IT to analyze data and string. We manage string, application data and the relationships between data and IT application.
Every dataset contains some errors, and every analyst experiences a rite of passage in wasting days drawing wrong conclusions because the errors have not been first rooted out.  Up to half of the time needed for analysis is typically spent in "cleaning" the data.  This time is also, typically, underestimated.  Often, once a clean dataset is achieved, the analysis itself is quite straightforward.
Such demand is particularly feeling today in a market where the value of information is always greater but at the same time more and more complex to retrieve and to certify.  
 The data source frequently reach excessive levels of divergence and in order to guarantee their quality and utility of the users, especially those in business, they have to pass through the users themselves.
Dirty data has long been a AGE’s bugbear. But in today’s wired world, the costs and consequences of inaccurate information are rising exponentially. Throw in the complications arising from merging different data sets, as in the aftermath of a merger or acquisition, and the difficulties of data cleansing multiply.

• "The first step is to identify homonyms and synonyms," - Homonyms, are two or more different items with the same identifier. Synonyms are the same items with more than one identifier.
• Next, we employ data-profiling to crawl though the data.
• The third step is "fuzzy matching," look for duplicates and errors introduced by keyboard entry.
• Next step is data-profiling tool, which highlighted errors and inconsistencies. ASA tools provide easy-to-understand, computer-generated diagrams to spot unusual data formats that could be erroneous.
• We develop an enterprise wide view of your customers. In some cases, the demand for consistently clean data comes from the customers themselves, who want to see how their business is performing in real-time.

Even better than cleaning dirty data is making sure it can’t be soiled in the first place.