Researchmoz added Most up-to-date research on "2015 - 2030: Big Data Market: Opportunities, Challenges, Strategies, Industry Verticals and Forecasts" to its huge collection of research reports.
“Big Data” originally emerged as a
term to describe datasets whose size is beyond the ability of
traditional databases to capture, store, manage and analyze. However,
the scope of the term has significantly expanded over the years. Big
Data not only refers to the data itself but also a set of technologies
that capture, store, manage and analyze large and variable collections
of data to solve complex problems.
Amid the proliferation of real time
data from sources such as mobile devices, web, social media, sensors,
log files and transactional applications, Big Data has found a host of
vertical market applications, ranging from fraud detection to scientific
R&D.
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Despite challenges relating to privacy
concerns and organizational resistance, Big Data investments continue
to gain momentum throughout the globe. SNS Research estimates that Big
Data investments will account for nearly $40 Billion in 2015 alone.
These investments are further expected to grow at a CAGR of 14% over the
next 5 years.
The “Big Data Market: 2015 – 2030 –
Opportunities, Challenges, Strategies, Industry Verticals &
Forecasts” report presents an in-depth assessment of the Big Data
ecosystem including key market drivers, challenges, investment
potential, vertical market opportunities and use cases, future roadmap,
value chain, case studies on Big Data analytics, vendor market share and
strategies. The report also presents market size forecasts for Big Data
hardware, software and professional services from 2015 through to 2030.
Historical figures are also presented for 2010, 2011, 2012, 2013 and
2014. The forecasts are further segmented for 8 horizontal submarkets,
15 vertical markets, 6 regions and 35 countries.
Table of Content
1 CHAPTER 1: INTRODUCTION
1.1 Executive Summary
1.2 Topics Covered
1.3 Historical Revenue & Forecast Segmentation
1.4 Key Questions Answered
1.5 Key Findings
1.6 Methodology
1.7 Target Audience
1.8 Companies & Organizations Mentioned
2 CHAPTER 2: AN OVERVIEW OF BIG DATA
2.1 What is Big Data?
2.2 Key Approaches to Big Data Processing
2.2.1 Hadoop
2.2.2 NoSQL
2.2.3 MPAD (Massively Parallel Analytic Databases)
2.2.4 In-memory Processing
2.2.5 Stream Processing Technologies
2.2.6 Spark
2.2.7 Other Databases & Analytic Technologies
2.3 Key Characteristics of Big Data
2.3.1 Volume
2.3.2 Velocity
2.3.3 Variety
2.3.4 Value
2.4 Market Growth Drivers
2.4.1 Awareness of Benefits
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