Big Data in Telecom Analytics Market Outlook and Forecasts 2022 – 2030

Big Data in Telecom Analytics Market Outlook and Forecasts 2022 – 2030

This report assesses the correlation between global structured and unstructured data in conjunction with the telecom analytics market. The report also studies the business applications, vendor landscape, value chain analysis, case studies, and a quantitative assessment of the industry during 2022 to 2030.

Select Report Findings:

North America will lead the big data in telecom analytics market
Data management platforms will represent the highest revenue segment
Big data in telecom analytics market poised to reach $21.12 billion by 2030
IoT support in business specific application will grow at 23.1% CAGR during the period
Big data opens a vast array of applications and opportunities in multiple industry verticals
Big data enables multiple benefits for telecom companies including improvement of subscriber experience, maintaining of smarter networks, reducing churn ratio, and generation of new revenue streams

Big data tools help communications service providers gain deeper insights into customer behavior, including usage patterns, preferences, and interests. While hard to derive quick and meaningful insights, big data solutions provide carrier insights into relationships, family, work patterns and location. This is increasingly achieved in real-time using both structured and unstructured data.
The term big data refers to a massive volume of both structured and unstructured data that is so large that it is difficult to process using traditional database and software techniques. While the presence of such datasets is not something new, the past few years have witnessed immense commercial investments in solutions that address the processing and analysis of big data.

Big data opens a vast array of applications and opportunities in multiple vertical sectors including not limited to retail and hospitality, media, utilities, financial services, healthcare and pharmaceutical, government and homeland security and the emerging industrial internet vertical. With access to vast amounts of datasets, telecom companies are also turning out to be major proponents of the big data movement. Big data technologies offer a multitude of benefits to network operators which include improving subscriber experience, building and maintaining smarter networks, reducing churn and even the generation of new revenue streams.

Big data and analytics have emerged as a potential source of revenue for telecom operators, at a time when carriers have been feeling the pressure to generate new sources of revenue. One of those sources comes from their ability to mine the huge amount of data they generate or have access to in both their customer base and their networks. The two have emerged as the tools to help analyze and manage this information. There are now many analytical and intelligence tools that enable mobile operators to understand customer and network behavior.
Communications service providers have a rich stream of data, especially those that offer telephony, TV and Internet services, the triple play operators. The many sources of data are an advantage for telecom companies, but if they want to monetize that data and derive meaningful, actionable analytics it could be challenging due to the complexities of correlation, prediction, and the massive volumes of data from different sources.

Big data helps telecom providers to get deeper insights into customer behavior, their service usage patterns, preferences, and interests. While hard to derive quick and meaningful insights, big data gives telecom companies an idea of relationships, family, work patterns and accurate location data among others. The publisher of this report believes that this will optimally be performed in real-time using both structured and unstructured data.

Prior to leveraging big data analytics solutions, communications service provider ‘raw data’ represents unprocessed and uncategorized content that flows across the network, and ‘meta-data’, which is the data describing the properties, sources, costs, etc. relating to the content. In terms of data types, carrier data can be divided into two broad categories as structured and unstructured data. The blending of the two provide particularly helpful insights in terms of network and service optimization, cost reduction, and generation of new insights and information.

Companies in Report:

Accenture
Amazon
Apache Software Foundation
APTEAN
Cisco Systems
Cloudera
Dell EMC
ElectrifAI
Facebook
GoodData Corporation
Google (Alphabet)
Guavus (Thales Group)
Hitachi Data Systems
Hortonworks
HPE
IBM
Informatica
Intel
Jaspersoft (TIBCO)
Microsoft
MongoDB
MU Sigma
Netapp
Oracle
Pentaho
Platfora (Workday)
Qliktech
Rackspace Technology
Revolution Analytics (Microsoft)
Salesforce
SAP
SAS Institute
Sisense
Splunk
Sqrrl Data
Supermicro
Tableau Software
Teradata
Tidemark (Insight Software)
VMware