Global Big Data in Telecom Analytics Market Report 2021-2026: Focus on Compute Type, Deployment Type, Applications and Services –



DUBLIN – (COMMERCIAL THREAD) – The report “Big Data in Telecom Analytics by Computing Type, Deployment Type, Applications and Services 2021-2026” has been added to offer.

This report provides an assessment of the global structured data, big data and telecommunications analytics markets including a study of business drivers, application use cases, vendor landscape, value chain analysis , case studies and a quantitative assessment of the industry from 2021 to 2026..

Big data tools help communications service providers better understand customer behavior, including usage patterns, preferences and interests. While it is difficult to get quick and meaningful insights, big data solutions provide operators with information about relationships, family, work patterns, and location. This is increasingly done in real time using both structured and unstructured data.

The term big data refers to a massive volume of structured and unstructured data, so large that it is difficult to process using traditional database and software techniques. While the presence of such datasets is not something new, recent years have seen huge commercial investments in solutions that deal with big data processing and analysis.

Big Data opens up a vast array of applications and opportunities across multiple industry verticals including, but not limited to, Retail & Hospitality, Media, Utilities, Financial Services, Personal Care health and pharmaceuticals, government and homeland security and the emerging industrial Internet sector.

With access to vast amounts of datasets, telecom companies are also proving to be the main proponents of the big data movement. Big Data technologies offer a host of benefits to network operators, including improving the subscriber experience, building and maintaining smarter networks, reducing churn rates, and even generating new sources of service. income.

Big data and analytics has become a potential source of revenue for telecom operators at a time when operators are feeling the pressure to generate new sources of revenue. One of those sources comes from their ability to leverage the huge amount of data they generate or have access to both in their customer base and their networks. Both have emerged as the tools to help analyze and manage this information. There are now many analytics and intelligence tools that allow mobile operators to understand customer and network behavior.

Communication service providers have a rich data stream, especially those offering telephony, television and Internet services, triple play operators. Many data sources are an advantage for carriers, but if they want to monetize that data and gain meaningful, actionable analysis, it could be difficult due to the complexity of correlation, prediction, and massive volumes of data. data from different sources.

Big data helps telecommunications providers better understand customer behavior, service usage patterns, preferences and interests. While it’s hard to get quick and meaningful insights, big data gives telecom companies insight into relationships, family, work patterns, and precise location data, among other things. The editor of this report believes this will be best done in real time using both structured and unstructured data.

Before taking advantage of big data analytics solutions, the communications service provider’s ‘raw data’ represents the unprocessed and uncategorized content that circulates over the network, and ‘metadata’, which is the data describing the properties. , sources, costs, etc. contents. In terms of data types, supporting data can be divided into two broad categories as structured and unstructured data. The mixture of the two provides information that is particularly useful in terms of optimizing the network and services, reducing costs and generating new information and insights.

Select the report results:

  • Leading operators merge structured and unstructured data sources to gain new insights and insights

  • The operations of communications service providers depend on big data analytics solutions for up to 32% of all operator revenues.

  • Managed service providers in big data analytics space delivering data and information as a service to operators rely primarily on cloud-based solutions

  • The fastest growing component is the AI ​​and IoT Data Combination (AIoT), which represents a fusion of raw data derived from automation and advanced analytics powered by AI.

Main topics covered:

1.0 Executive summary

2.0 Big Data Technology and Business Case

2.1 Structured or unstructured data

2.2 Defining Big Data

2.3 Key characteristics of Big Data

2.4 Data capture through detection and social systems

2.5 Big data technology

2.6 Business Factors for Big Data and Telecommunications Analytics

2.7 Market barriers

3.0 Main Sectors of Big Data Investment

3.1 Industrial internet and M2M

3.2 Retail trade and hotels

3.3 Media

3.4 Utilities

3.5 Financial services

3.6 Health and pharmaceuticals

3.7 Telecommunications companies

3.8 Government and internal security

3.9 Other sectors

4.0 The Big Data Value Chain

4.1 Fragmentation in the Big Data value chain

4.2 Data acquisition and provision

4.3 Data warehousing and business intelligence

4.4 Analysis and virtualization

4.5 Action and management of business processes

4.6 Data governance

5.0 Big Data in Telecommunications Analysis

5.1 Telecommunications Analysis Market

5.2 Improve the subscriber experience

5.3 Building smarter grids

5.4 Unsubscribe / Risk reduction and new sources of income

5.5 Telecommunications Analysis Case Studies

5.6 Operators, Analytics and Data as a Service (DaaS)

5.7 Opportunities for Operators in Cloud Analytics

6.0 Structured data in Telecom Analytics

6.1 Data sources and telecommunications repositories

6.2 Telecom data mining

6.3 Telecommunications database services

6.4 Analysis of structured telecom data

7.0 Analysis of Certain Big Data Market Players

7.1 Supplier evaluation matrix

7.2 Apache Software Foundation


7.4 Amazon

7.5 APTEAN (formerly CDC Software)

7.6 Cisco systems

7.7 Cloudera

7.8 Dell EMC

7.9 Facebook

7.10 GoodData Corporation

7.11 Google (alphabet)

7.12 Guavus (Thales Group)

7.13 Hitachi data systems

7.14 Hortonworks

7.15 HPE

IBM 7.16

7.17 Computing

7.18 Intel

7.19 Jaspersoft (TIBCO)

7.20 Microsoft

7.21 MongoDB (formerly 10Gen)

7.22 MU Sigma

7.23 Netapp

7.24 ElectrifAI (formerly Opera Solutions)

7.25 Oracle

7.26 Pentahon

7.27 Platform (working day)

7.28 Qliktech

7.29 Rackspace technology

7.30 Analytics Revolution (Microsoft)

7.31 Sales force

7.32 SAP

7.33 SAS Institute

7.34 Sisense

7.35 Splunk

7.36 Sqrrl data

7.37 Supermicro

7.38 Table software

7.39 Teradata

7.40 Tidemark (Insight software)

7.41 VMware

8.0 Big Data in Telecommunications Analysis Forecast 2021 to 2026

8.1 Global Big Data in Telecommunications Analysis 2021 – 2026

8.2 Big Data in Telecommunications Analysis by Region 2021 – 2026

8.3 Big Data Products and Services in Telecom Analytics 2021 – 2026

8.4 Big Data management platform for telecoms 2021 – 2026

8.5 Big Data Services for Telecommunications Analytics 2021 – 2026

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