My presentation at ICE2023 about Big data. You can watch it on YOUTUBE
- What is Big Data?
1.1 Volume
1.2 Velocity
1.3 Variety
1.4 The difference to traditional data - Applications
2.1 Politics: How Obama Won with Big Data
2.2 Health Care: How Google Tracks Flu's Spread
2.3 Finance: Customer Experience - Challenges and Solutions
3.1 Challenges
3.2 Solutions - Conclusion
Big Data refers to large and complex datasets challenging to process with traditional techniques. It's characterized by volume, velocity, and variety.
This represents the sheer amount of data. Big data can range from several terabytes to petabytes, challenging traditional data processing capabilities.
Velocity refers to the speed at which data grows and is processed. It includes a rapid increase in data volume and real-time data processing.
Unlike traditional structured data, Big Data includes unstructured data like documents, images, videos, and sensor data, allowing diverse data analysis.
Big Data differs from traditional data in its scale, speed, and variety, posing challenges and requiring advanced processing techniques.
The Obama presidential campaigns leveraged Big Data for targeted outreach, fundraising, voter turnout, and social media engagement, setting a precedent for data-driven political strategies.
Google Flu Trends utilized aggregated search data to create an early warning system for flu outbreaks, supplementing traditional surveillance methods. Despite its effectiveness, it faced criticism and was later replaced.
In finance, predicting customer churn using Big Data allows personalized retention efforts, reducing costs and improving overall customer experience.
Large data volumes increase vulnerability to breaches, risking loss or theft of sensitive information, leading to financial loss and reputational damage.
Big Data analytics, involving extensive personal data, raises privacy concerns. Compliance with data privacy laws and obtaining consent is crucial.
Big Data analytics may perpetuate biases if the underlying data is biased. This can negatively impact marginalized groups.
Adherence to privacy policies and regulations ensures lawful handling of user data by big companies.
Implementing robust security measures, such as firewalls and intrusion detection systems, protects against data breaches.
Companies inform users about data practices, obtain consent, and provide control options over privacy settings.
Anonymizing data by removing personal identifiers safeguards user privacy during analysis.
Utilizing encryption methods protects personal information from unauthorized access.
In conclusion, Big Data is akin to fire – powerful but requiring careful handling. Its applications span politics, healthcare, and finance, revolutionizing decision-making. However, challenges like data breaches and biases necessitate robust solutions through regulations, security measures, and ethical data practices.
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