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Legacy Data Migration and Frauds detection using Blu Age and Big Data

Legacy information systems (‘70, ‘80, ‘90…) of many organizations are huge friable data sets (flat files with odd structuring, non-classical databases…). For example, tax frauds detection for a public institution is the timely processing of complex requests across Big Data environments, which is possible with computing infrastructures and technologies like those proposed by DICE.

Old technologies make frauds more complicated to be detected Tax evasion and frauds represent a huge problem for governments, causing them a big loss of money each year. The EU estimates the sums are being lost due to tax evasion and avoidance of the order of € 1 trillion. In Italy alone, an estimated €285 billion taxes remained unpaid in 2012, about 18% of GDP. However, detecting frauds is actually a difficult and challenging task because of the high number of tax operations performed each year and the differences inherent in the way the taxes are calculated in each country. With the availability of massive amounts of structured and unstructured information, data organization and analytics are a promising solution to find anomalies and uncover potential violations. Potentially enough to enable fraud detection systems which scale up to the huge volume of data to process. Governments are increasingly using Big Data in multiple sectors to help their agencies managing their operations, and to improve the services provided to citizens and businesses. In such context it is obvious that Big Data solutions has the potential to make tax agencies faster and more efficient. Unfortunately, most public organizations are still using legacy information systems that don’t support the recent Big Data platforms and where the data is highly duplicated, scattered, even diluted (e.g. resulting from COBOL programming style) without any consolidated view, no correlation, no explicit semantics and with ineffective naming conventions. Migrating legacy databases using Blu Age Using Big Data technologies implies an unavoidable step of gathering data which most of the time consists on migrating the legacy database schema and data into a relational database. Netfective Technology released Blu Age Data and Database Modernization, a tool set that automates the migration of legacy databases and data toward structured Data Base schema and standardized format. This product enables complete modernization of both the data format and the database schema which is a great help when you have to normalize such legacy environments. “The point to be made here is that migrating data from such systems into a modern platform can be a tedious task, and the process can be risky, expensive and disruptive. Because of those limitations, Netfective Technology delivers a turnkey solution, called Blu Age, to industrially modernize any strategic business application freeing it from aging technologies and opening the way to new functionalities with highly improved economics,” said Alexis Henry, Head of Research at Netfective Technology. Adopt DICE and rapidly prototype a solution Netfective Technology, as a partner in DICE, is providing a functional and technical demonstrator. This goal is achieved through building a software prototype to illustrate the added value of Big Data in e-government applications especially for fraud detection. This demonstrator is based on a dedicated meta model conceived specifically for being realistic (features could apply to a real system), generic (features and data models could apply to multiple government agencies) and neutral (data are generated in order to protect citizens and businesses privacy). At this stage of the DICE project the meta model describes a taxpayer, and the data generator produces realistic information with hundreds of related attributes (name, address, ID card number, marital status, birthday, social security number...). This demonstrator will avoid any privacy/confidentiality issues since processed random data which are produced in such way to be anonymous and not refer to real persons. This demonstrator will process data record instances (millions) complying with the model described above. Utilizing Big Data and cloud processing technologies through DICE will be the key feature of the demonstrator. More information is available on our official websites: - -


DICE, Big Data, modernization, cloud computing, Blu Age