The Internal Revenue Service
The Internal Revenue Service (IRS) is the U.S public agency that collects taxes and implements tax laws. Since its inception in 1860s, IRS has grown relative to America’s population. IRS has processed many individual tax returns, especially in 2006, when it processed almost 134 million returns.
Nevertheless, the IRS, Sybase and other unscrupulous Americans have joined hands to implement a data warehouse called Compliance Data Warehouse (CDW). This warehouse has enhanced efficiency and more money is being collected from the taxpayers.
The data warehouse was important for the IRS because there were loads of accumulated information such as personal and tax information. Initially, the data was stored in older systems that were organized in many ways.
The data was stored in hierarchical mainframe databases, flat files or other relational databases. However, it was not easy to query and analyze data, especially from flat files, and that is why the IRS together with the group decided to implement the CDW, which allows flexible queries in the large database used in the whole world. CDW is a relational database and has billions or rows and many columns that contain complex links to many schedules.
The database enables the IRS researchers to search billions of records by use of a centralized source instead of multiple conflicting sources. CDW has enabled IRS to recover billions of dollars from the tax returns that was lost under the legacy system. The CDW is able to hold many terabytes of data and allow data access using many tools (Laudon and Laudon 252).
Despite the CDW having many benefits, its implementation was complicated, especially converting the old data to the new system since the data was not consistent.
In addition, persuading organizations to upgrade their system was not an easy task. Despite of all these challenges, the implementation was successful. After implementation, IRS got a 200-1 ratio of tax returns. The CDW also detected many mistakes in tax returns because it is able to determine organizations or people who cheat on taxes. CDW has reduced time to trace mistakes from eight months to just a few hours.
Data transportation was upgraded from using tapes to using a 2-terabyte network with attached storage applications. These storage devices are encrypted to make the data safe during transportation whereas the legacy tapes were not safe. Audits have proved that CDW is working well because it detects tax cheats. The IRS has minimized tax audits on honest taxpayers and has increased audits on the people whose tax information is at fault (Laudon and Laudon 252).
In essence, it was not easy to analyze the taxpayer data because there was no ease and speed in the way of detecting mistakes in tax returns. In addition, it was not easy to query and analyze data in the legacy system.
The technological challenge that IRS encountered was conversion of data from legacy to the new system because the structure of IRS data was not reliable due to its change from year to year. Management of data using CDW was another challenge because IRS had never handled such large amounts. Convincing organizations to upgrade their old systems and adapt to data warehouses was also a challenge and more so to government agencies.
Moreover, due to speed and ease with which the CDW was able to detect mistakes and cheats, it was easy for IRS to tell the people who are not honest with their tax returns. This enabled them to do more audits on information of such people and fewer audits on innocent taxpayers.
Other federal sectors where data warehouses are useful include justice, education, national aeronautics, space management and departments of defense. The data warehouses are useful in these sectors because they are used to detect fraud, abuse, evaluate research and scientific information, detect illegal activities and criminal patterns and detect terrorist tricks or activities.
Laudon Kenneth and Jane Laudon. Management Information System: Managing The Digital Firm. 11th ed. Upper Saddle River, NJ: Pearson, Prentice Hall, 2009. Print