Data Technologies



Data Technologies

Unstructured (Big) data represents about 90% of all data in today’s organizations. Many companies are using Big Data and Analytics in innovative ways. For example, some companies involved with consumer credit are using various methods to improve their business operations, which ultimately may result in many different improvements such as better fraud scoring and faster delivery of services.

Recognizing the complexities and issues associated with Big Data, some leading companies are offering Data as a Service (DaaS) and/or more precisely Big Data as a Service (BDaaS).

DaaS is defined as any service offered wherein users can access vendor provided databases or host their own databases on vendor managed systems. DaaS is expected to grow significantly in the near future due to a few dominant themes including cloud-based infrastructure/services, enterprise data syndication, and the consumer services trend towards Everything as a Service (XaaS). In addition, vendor managed systems provide necessary scalability and security for sustainable services execution.

The global application development community is becoming increasingly aware of Telecom Application Programming Interface (API) as a means of accessing data for a variety of communications-enabled applications. Telecom Network APIs capitalize on existing network infrastructure and platforms to facilitate new business opportunities for global CSPs to offer Business-to-Business (B2B) services in a DaaS basis.

Recognizing that the need to generate new high-margin revenue streams, leading CSPs are seeking new revenue models based on leveraging their network and subscriber data assets. Telecom Data as a Service (TDaaS) is one of those new models in which CSPs offer DaaS to various third party businesses on an anonymized basis.

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