Big Data and data management in the company

Big Data and data management in the company

Big Data is a value for the companies, but their use, which follows a market imperative rather than a necessity, requires the presence of Hadoop, only realistic data management solution, also to take into account in projects Data Warehouse.

Big Data is to be incorporated into the business environment and analytical data warehouse. But to do so you may need to enter your understanding. To do this, Big Data can be approached from the tetra-dimension of its facets:

Data at rest : the ready to be processed, all that information that already has volumes can occupy even reach exabytes and consider requiring additional storage requirements and data management.

Data movement : the creation and processing of data is a continuous flow, the nature today’s competitive environment requires periods of no response in excess of milliseconds. The data to be managed in real time, as generated, without waiting to be stored. Examples include sensors, fraud information, etc. and IBM InfoSphere Streams solution.

Big Data is a value for the companies, but their use, which follows a market imperative rather than a necessity, requires the presence of Hadoop, only realistic data management solution, also to take into account in projects Data Warehouse.

Big Data is to be incorporated into the business environment and analytical data warehouse. But to do so you may need to enter your understanding. To do this, Big Data can be approached from the tetra-dimension of its facets:

Data at rest: the ready to be processed, all that information that already has volumes can occupy even reach exabytes and consider requiring additional storage requirements and data management.

Data movement: the creation and processing of data is a continuous flow, the nature today’s competitive environment requires periods of no response in excess of milliseconds. The data to be managed in real time, as generated, without waiting to be stored. Examples include sensors, fraud information, etc. and IBM InfoSphere Streams solution.

Diversity of data: data that will be analyzed are stored in different sources of very diverse typology (information from logs, facebook, twitter, etc.), it provides an unprecedented wealth of analysis resulting in an extremely realistic picture and details of the situation of the company at present.

Doubtful data: is the darker side. Big Data. This uncertainty is due to two factors, inconsistency and incompleteness of the data that may be caused by latency, ambiguities, interpretations or human errors Recover or gain integrity these volumes of information requires a data management strategy appropriate .

Big Data and Hadoop in data management in data warehouse projects

Distinguish the incalculable contribution of Big Data for the company to recognize the importance of Hadoop , a concept that involves:

  • A framework for development and execution environment for applications capable of processing large amounts of data (Big Data).
  • The creation of a batch type and complications of intensive reading.
  • Google technology as a base.

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