Disruptive Big Data Applications in South Africa

Assessing the Use of Big Data Solutions in Local Industries

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Although South Africa is in a nascent phase regarding the adoption of Big Data technologies, industries have begun implementing Big Data solutions for improved operational processes and to find new business opportunities. The key driving forces behind Big Data discussed in this analysis include increased connectivity and Internet usage, for both mobile and machine-to-machine (M2M) communications; growth in cloud services; the continued desire for African insights; and reducing costs associated with Big Data solutions. This analysis focuses on the Big Data solutions market as it stands in 2016, with detailed analyses on industry adoption and uses, as well as the expectations for the market in South Africa.

Table of Contents

1. Executive Summary
Key Findings
2. Market Overview
Research Aim and Objectives
Research Scope—Ecosystem
3. What is Big Data?
The Characteristics of Big Data
Primary Characteristics of Big Data
Secondary Characteristics of Big Data
Primary Forces Enabling Big Data
The Value Chain for Big Data Solutions
4. Data Acquisition
Sources of Big Data
5. Data Management—Storage and Processing
Data Storage Options
Traditional Storage
Hybrid Storage
Cloud Storage
Data Storage—The Shift to Cloud-based Services
Data Processing—Batch versus Streamed
6. Data Analytics
Data Analytics
Data Analytics—Global Snapshot
7. Market Drivers and Restraints
Market Drivers
Increased connectivity and Internet usage, such as M2M, IoT, and smartphones
Growth of cloud services
Reducing costs associated with Big Data
Desire for African insights
Market Restraints
Lack of appropriate skills and knowledge
Existing infrastructure and data sources
Weakness of the local economy
Unconvincing business case
Concerns about data security and respecting privacy
8. Industry Outlook
Global Big Data Adoption by Industry
Big Data Solutions—Automotive and Logistics
Big Data Solutions—Extractive Industries
Big Data Solutions—Telecommunications
Big Data Solutions—Healthcare
Big Data Solutions—Retail
Big Data Solutions—Public Sector
Big Data Solutions—Financial Services and Insurance
Big Data Solutions—Entertainment Industry
Innovative Participants in the South African Market
9. The Outlook for Big Data Solutions in South Africa
Introducing the SKA
Applying the Big Data Value
The Impact of the PoPI Act
Incorporating Machine Learning and Artificial Intelligence (AI)
10. Conclusion
The Last Word
Legal Disclaimer
11. Appendix
Research Acronyms
Research Acronyms—Measures of Data Size
12. The Frost & Sullivan Story

List of Figures & Charts

1. Big Data Solutions Market: Market Drivers, South Africa, 2016–2022
2. Big Data Solutions Market: Market Restraints, South Africa, 2016–2022
3. SKA Data Analysis Process, South Africa, 2016
4. Convergence Between Machine Learning, AI, and Big Data, Global, 2016

1. Big Data Ecosystem, Global, 2016
2. Major ICT Trends, Global, 2016
3. Big Data Value Chain, Global, 2016
4. Big Data Value Chain Explained, Global, 2016
5. Big Data Solutions Market: Notable Participants, South Africa, 2016
6. The Complexity of Data, Global, 2016
7. Big Data Sources, South Africa, 2010–2020
8. Batch or Stream Data Processing, Global, 2016
9. Four Types of Data Analytics, Global, 2016
10. Data Analytics Market: Per cent Revenue Breakdown, Global, 2015
11. Big Data Solutions Market: Revenue Breakdown by Vertical Market, Global, 2014

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