The landscape of data gathering and analysis is rapidly changing as the amount of data generated in conjunction with data sources and means of extracting data continues to accelerate. One of the key issues is how to most efficiently and effectively realize value from this seemingly boundless sea of unstructured (Big) data.
Big Data is much more than its technical definition implies: A collection of data sets so large and complex that it becomes difficult to process using on-hand database management tool. Big Data is already changing the way business decisions are made since big data exceeds the capacity and capabilities of conventional storage, reporting and analytics systems, it demands new problem-solving approaches.
Business Intelligence (BI) represents a set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. BI has existed in various forms for a long time but arguably is lacking when it comes to unstructured data.
This research evaluates the relationship between BI and Big Data including benefits, issues, and challenges in terms of planning and integration. The report also answers important questions such as:
- Is BI being replaced by Big Data approaches?
- How is Big Data clouding Business Intelligence?
- What are the important steps in BI-Big Data integration?
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- Understand why we can't ignore Big Data, and what new insights Big Data can provide that BI can't today
- look at limitations and risks involved in handling large unstructured data for better business decision making
- Learn why there is a need to marry Big Data and BI solutions and the associated benefits and challenges
- Learn the questions every organization should consider and find answers to them in order to overcome the roadblocks in implementing new data technologies that make the Big Data ecosystem
Table of Contents
1.0. EXECUTIVE SUMMARY
- 1.1. OVERVIEW
- 1.2. KEY BENEFITS
- 1.3. QUESTIONS ANSWERED BY REPORT
- 1.4. TARGET AUDIENCE
2.0. INTRODUCTION TO BIG DATA
- 2.1. DATA EXPLOSION
- 2.2. DATA FROM INSIDE AND OUTSIDE
- 2.3. WHAT IS BIG DATA?
- 2.4. THE V'S OF BIG DATA
- 2.5. A SAMPLING OF BIG DATA FACTS
- 2.6. WHY ONE CAN'T IGNORE BIG DATA
- 2.7. BIG DATA MARKET
- 2.8. MARKET CONDITIONS THAT ARE DRIVING BIG DATA ADOPTION
- 2.9. TECHNOLOGY TRENDS INFLUENCING BIG DATA ADOPTION
3.0. BIG DATA: OPPORTUNITIES AND CHALLENGES
- 3.1. OPPORTUNITIES AND REWARDS
- 3.2. BUSINESS CASES AND EXAMPLES
- 3.3. BUSINESS IDEAS TO CAPITALIZE ON HUMONGOUS DATA
- 3.4. BIG DATA'S BIG PROBLEMS
- 3.5. BIG DATA REGULATION
- 3.6. BIG DATA TRENDS 2014
- 3.7. BIG DATA TALENT REQUIREMENT
- 3.8. THE NEW DATA SCIENTIST
- 3.9. TIPS FOR WINNING OVER BIG DATA TALENT SHORTAGE
4.0. PUTTING BIG DATA TO WORK
- 4.1. BIG DATA ANALYTICS PIPELINE
- 4.2. BIG DATA ECOSYSTEM
- 4.3. GETTING STARTED WITH A BIG DATA PROJECT
- 4.4. BEST PRACTICES IN BIG DATA SUCCESS
5.0. BUSINESS INTELLIGENCE (BI)
- 5.1. HOW BIG DATA IS CLOUDING BUSINESS INTELLIGENCE
- 5.2. HOW IS BI GETTING IMPACTED?
- 5.3. PREDICTIONS FOR BUSINESS INTELLIGENCE
- 5.4. KEY BUSINESS INTELLIGENCE SOLUTIONS PROVIDERS
6.0. BI AND BIG DATA INTEGRATION
- 6.1. ADVANTAGES OF BI-BIG DATA INTEGRATION
- 6.2. CHALLENGES IN BI-BIG DATA INTEGRATION
- 6.3. APPROACHES FOR INTEGRATING BIG DATA PLATFORM WITH BI INFRASTRUCTURE
- 6.4. THREE STEPS TO BI-BIG DATA FRAMEWORK
7.0. CONCLUSIONS AND RECOMMENDATIONS
List of Figures
- Figure 1: How the Internet is Collecting Data
- Figure 2: The V's of Big Data
- Figure 3: Big Data Market Forecast, 2011-2017 ( in $US Billion)
- Figure 4: Market Conditions Driving Adoption of Big Data
- Figure 5: Strategies for Making Data Profitable
- Figure 6: Big Data's Darker Side
- Figure 7: Key Regulatory Areas for Big Data Growth
- Figure 8: Big Data Talent Requirement
- Figure 9: Demand Supply Gap for Data Scientists
- Figure 10: Who is the New Data Scientist?
- Figure 11: Winning Over the Talent Shortage
- Figure 12: Big Data Analytics Pipeline
- Figure 13: Big Data Ecosystem
- Figure 14: Getting Started with Big Data
- Figure 15: Best Practices in Big Data Success
- Figure 16: Challenges in Integration of BI and Big Data Systems
- Figure 17: Approaches to Integrating BI Infrastructure to Big Data
- Figure 18: BI Big Data Framework
- Figure 19: Three Steps to Bi Big Data Framework
- Figure 20: Global Big Data Revenue 2014 - 2019
- Figure 21: Big Data Revenue by Region
List of Tables
- Table 1: Key Differences between BI & Big Data Analytics