Big Data: A road map for business intelligence

Big Data: A road map for business intelligence

Code: ML-ML00019-004 | Published: Mar-2015 | Pages: 24 | MarketLine
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Big Data has been hailed as a ground-breaking technological development that will revolutionize how businesses operate. Major corporations have therefore been quick to exploit the opportunities available. Understanding how companies have used Big Data and where Big Data might be used next is therefore vital to keeping pace with the strategic advantages being gained in the modern world.



Key Findings
- A detailed explanation of the predominant framework used to undertake Big Data analytics, from a business intelligence perspective.
- An overview of the key players in the industry.
- A detailed analysis of the uses of Big Data in terms of business intelligence, with real-life industry examples.
- Forward looking analysis of the potential uses of Big Data in terms of business intelligence.
- An overview of the limitations of Big Data and the proposal of a new form of holistic intelligence.

Reasons To Buy
What is Big Data, how does it work and why does it matter?
Who are the key players in the industry and what do they offer?
How has Big Data been used in the past and how might it be used in the future?

Table of Contents

OVERVIEW
Catalyst
Summary
THE CORE TECHNOLOGIES AND THE KEY PLAYERS
The core technologies are open and free but complex to operate
Open source software has been central to the development of Big Data
How can a business make sense of Big Data and why does it matter?
How does Big Data really work?
Hadoop Common
The Hadoop Distributed File System (HDFS)
Hadoop YARN
Hadoop MapReduce
The key players include software majors and rising upstarts
Technology powerhouses are likely to reap the most rewards in the long-term
The new and the hungry have seen exponential growth but not all can be winners
EARLY ADOPTERS HAVE BEEN INTROSPECTIVE
Customer-generated information has provided many new strategic insights
Customer analytics gives businesses greater predictive power
Sentiment analysis can be used to tailor public interactions and optimize production processes
Analysis of the general public can lead to improved cost and time efficiencies
Company processes and operational information become clearer with Big Data
Previously impenetrable research and development problems have become solvable
Industrial usage points to huge cost savings through optimization techniques
BIG DATA 2.0 - HOLISTIC INTELLIGENCE
Where do we go from here?
What happens when everyone is using Big Data?
Sourcing external data is a logical next step in the short-term
CONCLUSIONS
The future belongs to those who ask the right questions
APPENDIX
Definitions
Sources
Further Reading
Ask the analyst
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