Big Data Applications, Challenges and Opportunities
Big data has increased the demand of information management so much that most of the world’s big software companies are investing in software firms specializing in data management and analytics. According to one rough calculation, one-third of the globally stored information is in the form of #alphanumeric text and #still image data, which is the format most useful for most big data applications. Since most of the data is directly generated in digital format, we have the opportunity and the challenge both to influence the creation to facilitate later linkage and to automatically link previously created data. There are different phases in the Big Data analysis process and some common challenges that underlie many, and sometimes all, of these phases.
- Ecommerce and customer service
- Security and privacy
- Manufacturing
- Telecommunication
- E-Government
- Public administration
- Big Data Analytics in Enterprises
- Retail / Consumer
- Travel Industry
- Current and future scenario of Big Data Market
- Financial aspects of Big Data Industry
- Clinical and Healthcare
- Regulated Industries
- Biomedicine
- Finances and Frauds services
- Web and Digital Media
- Data Integration, Aggregation, and Representation
- Heterogeneity and Incompleteness
- Scale, Timeliness and Privacy
- System Architecture and Human Collaboration
- New innovations and business opportunities
- Query Processing, Data Modeling, and Analysis
- Business Proliferation
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Big Data Applications, Challenges and Opportunities Conference Speakers
Recommended Sessions
- Artificial Intelligence
- Big Data Analytics
- Big Data Technologies
- Business Analytics
- Cloud Computing
- Clustering
- Data Mining Methods and Algorithms
- Forecasting from Big Data
- Internet of Things (IOT)
- Nanoinformatics
- New Visualization Techniques
- Renewable Energy Forecasting with Big Data
- Social Network Analysis
- Big Data Algorithm
- Big Data Applications, Challenges and Opportunities
- Big Data in Nursing Research
- Big Data Optimization
- Complexity and Algorithms
- Data Mining and Machine Learning
- Data Mining Applications in Science, Engineering, Healthcare and Medicine
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- Data Privacy and Ethics
- Data Warehousing
- Frequent Pattern Mining
- Open Data
- Search and Data Mining
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