Why Entity resolution is an essential element of BIG DATA field

The process of identifying records by processing a data set representing the same real world entity is known as entity resolution. Entity resolution is an important part of information integration.The resolution comes from the word “solution”, because in the process it is necessary to decide to solve the problem, they indicate references to one, or to different objects. This definition can be successfully applied not for two, but for a set of references. In this case, the links can be aggregated into subsets,or clusters.

Entities are described by their attributes. Identifying attributes (identity attributes) are those that, when taken together, make it possible to distinguish one entity from another. For a person this name, address, date of birth, fingerprints is what is asked when filling out a driver’s license or when contacting a clinic. The degree of completeness (completeness), accuracy, timeliness, reliability, consistency, accessibility, and other indicators of referential data affect the operation of resolving entities and leads to better or worse results. This is one of the reasons why the resolution of entities (ER) is so strongly related to the quality of the data (information quality, IQ).

Why Entity resolution software?

Entity Resolution software supports probabilistic direct matching, transitive link, and asserted link, entity resolution system. It constructs a system that promotes exploration for matching candidates and maintains an index of the value of id attribute in memory. Since there is an id management system, persistent identifier identifiers are also supported. Software is to incorporate unique entity Id information management among other ER system. Provide a way to apply identifiers over the lifetime of persistent Id.

Benefit of  Entity resolution software

  1. Elimination of ambiguity of identification data – Who is who. Accumulating the contextual data associated with identification over time, entity resolution software uses various corporate sources of information to establish and verify the identity. Entity Resolution objects identification technology analyzes these attributes at different points in time, providing the most accurate identification and determining the need to adjust the assumptions made earlier based on new facts.
  2. Eliminating the ambiguity of the relationships – Who knows whom. After an accurate identification of the individual, complex relationships can be identified. Entity Resolution processes the analyzed identity data in order to establish existing or past relationships of any kind between people.
  3. Processing complex events –Who does what. Having reliable data on “who is who” and “who knows who,” Entity Resolution applies mechanisms for processing complex events to evaluate all the actions of the object and, if necessary, related objects. The ability to find in the information array all the phenomena associated with the same person is required to get a clear picture of his activities within the organization. Thanks to this complex function, the software solution can detect even carefully disguised fraudulent and criminal actions.

Methods for entity resolution

The joint business resolution process, which is fully performed by the software solution, includes four stages: identifying, solving, referring and scoring.

  1. Recognition (Extraction) – In the first stage, it must recognize the data from the collection, validation, optimization and improvement of incoming identity data. This phase were made to clean and protect standardization of data values, and the data integrity of the company’s database. Usually it can be completed at the data collection and preparation phase.
  2. Resolve (Deduplication) – To solve at the second stage, the process identities in facilities that sophisticated applications many algorithms to compare the data values ​​in the incoming identity record against existing institutions in the entity database to determine if it belongs to the same unit. If the appropriate facility or facilities have been dissolved, they will be enriched by new record. Otherwise, the incoming identity forms new entity in the database. The strongest challenges will be: name ambiguity, data quality and heterogeneity, clustering methods.
  3. Relate – In the third stage, complete recognition process has also been the relationship that captures relationships between identities and organizations and warnings for relationships of interest. In this case, the strongest task will be to take the right rules and algorithms defined for an entity hierarchy.
  4. Scoring (exam) – At the fourth level, the system calculates how closely the attributes for an incoming identity match the attributes of an existing business. The results of this analysis are computational values ​​that the system uses to solve corporate identities and recognize relationships between entities.

The Entity Resolution is one of the most demanding in the field of Big Data. Businesses have a great and unique experience here and will be happy to answer your question and help solve your business task. Entity resolution is an important part of information integration that aims to discover records from one or more data sources describing the same real world object. The dissertation presents step-by-step procedures that solve several sub-problems of MapReduce-based execution of Entity Resolution workflows. Entity resolution techniques typically compare pairs of records using multiple similarity measures. In recent years, the newly created paradigm Infrastructure as a Service has created the IT world changed massively. The provision of computing infrastructure by external service providers provides the ability to quickly, if necessary, a large amount of processing power, storage space and acquire bandwidth without upfront investment. At the same time, both the amount of freely available increases as well as the data to be managed in companies dramatically. The need for efficient data management and evaluation of these data volumes required further development of existing ones IT technologies and led to the emergence of new research areas and a host of innovative ones Systems. A typical feature of these systems is distributed storage and data processing in large computer clusters consisting of standard hardware. Especially the entity resolution softwarehas become increasingly important over the years. Itallows distributed processing of large amounts of data and abstracts from the details of the distributedcalculating and handling hardware errors. Entity resolution is an important part of information integration, whose goal is the discovery of records from one or more data sources, the same real world object describe.

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