The Power of Data — Big Data in Risk Management
Introduction
The presence of big data is mainly driven by the growing number of information resources and increasing technology usage. Big data enables building real-time systems, processing optimizations, and system performance control for both providers and customers.
What is Big Data?
"Big Data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze." — McKinsey Global Institute
Big data is an evolving term describing large volumes of structured, semi-structured, and unstructured data that can be mined for information and used in machine learning projects and advanced analytics applications.
Key Advantages of Big Data Analytics
Cost Reduction
Technologies like Hadoop and cloud-based analytics bring significant cost advantages for storing large data volumes and identifying more efficient business operations.
Faster and Better Decision Making
In-memory analytics combined with the ability to analyze new data sources enables immediate, evidence-based decisions.
New Products and Services
Analytics help understand customer interests, enabling businesses to create targeted new products and services.
Big Data Technologies
- Apache Hadoop (HDFS): Splits files into large blocks distributed across nodes, processing data in parallel.
- Apache Spark: In-memory processing engine for real-time analytics.
- Cloud Solutions: Amazon EMR, Microsoft Azure HDInsight, Google Cloud Dataproc.
- NoSQL Databases: For applications requiring high flexibility and scalability.
Big Data Security Risks
Key Security Threats:
- • Big data breaches and malicious attackers
- • Data manipulation and unauthorized disclosure
- • Ransomware attacks on centralized data stores
- • Regulatory compliance challenges (GDPR and data protection laws)
Big Data Statistics
2.5 Quintillion Bytes
of data is created every single day (Forbes, 2018)
Almost 90% of all data in the world was generated in just the last two years.
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