GB979D Big Data Analytics Big Data Repository R17.0.1

The Analytics Big Data Repository (ABDR) is a project of the TM Forum, focused on the definition of data entities for specific analytical scenarios identified for the CSP. The ABDR is a concept developed and specified by the TM Forum to support the creation of standardized implementations across operators, and straightforward re-usability of data by ABDR compliant solutions.

At a logical level the ABDR is a data dictionary, defining entities based on analytics scenario considered by the members during development. At an implementation level, the data entity definition provides a high level construct for the data structure/ mechanism to be created to support specific business questions.

Many systems have been designed over time in order to deal with analytics of large sets of data, each with their own objectives and operating environments. Big data analytics (BDA) represents a specific – and novel – set of goals and challenges that lead to particular approaches to projects, data organization and platform criteria.

This Addendum will develop the notion of an ABDR dictionary and explore the specificity of big data analytics, especially with respect to other analytics technologies and approaches such as those related to Enterprise Data Warehouse or Hadoop type platforms. The term ABDR will be used to encompass both organizational and technological related topics since they are intertwined.

The Addendum starts with a review of the successive generations of platforms and highlights trade-offs that ABDR architects and users face. The TM Forum has conducted extensive research in the area of Big Data Analytics, and this document, GB979D, builds on that research by illustrating how the main challenges of big data analytics imply new approaches that are emerging as the maturity in this domain develops.

The Addendum will conclude with some considerations on the current trends and perspectives for big data analytics, as this domain is still in an early stage of development.

General Information

Document series: GB979D
Document version: 4.0.2
Status: TM Forum Approved
Document type: Best Practice
Team approved: 05-Jun-2017
IPR mode: RAND
TM Forum Approved: 13-Nov-2017
Date modified: 22-Nov-2017