1. Introduction

• Importance of Foreign Trade : Developments in the global economy and the role of countries in their growth.
• Definition of Data Analytics and Decision Support Systems : How are there different designs in foreign trade with modern technologies?

2. The Role of Data Analytics in Foreign Trade

• Definition of Data Analytics : Characteristics and interpretation of structured and unstructured data.
• Types of Foreign Trade Data : Export-import data, logistics data, customer development, market trends.
• Data Sources :
  • Customs and foreign trade reports
  • Data from international trade organizations (UN Comtrade, ITC etc.)
  • Big data platforms (web browsing, social media, news).
• Turkish: Analysis :
  • Analysis of which parts of which intervals.
  • Configuration of the pricing configuration.
  • Competitive analysis.

3. Decision Support Systems (DSS)

• Definition and Importance of KDS :
  • Systems that guide executives through the details of decision making.
• Components of DSS :
  • Data management: Storing and applying data.
  • Analytical tools: Business intelligence and visualization tools.
  • Modelling: Scenario analysis and predictive models.
• Areas of Use :
  • Access chain management.
  • Market use efficiency.
  • Risk analysis (e.g. currency exchange rates and geopolitical risks).

4. The Impact of Big Data and Artificial Intelligence

• The Role of Big Data in Foreign Trade :
  • Making predictions with larger data sets.
  • Process development in logistics and supply chain.
• Machine Learning and Artificial Intelligence (AI) :
  • Predictive models: Export markets and demand forecasting.
  • Automation: Intelligent trade and customs details.
• Blockchain Technology :
  • Ensuring transparency and security in commercial transactions.

5. Sample Applications

• Sectoral Applications :
  • Export of agricultural products.
  • Business trends in the technology and electronics industry.
• Successful Strategies :
  • Data analysis of platforms such as Amazon and Alibaba has been simplified.
• Türkiye Example :
  • The role of data analytics in Turkey's export process.
  • Prominent sectors: Textile, automotive, defense industry.

6. Challenges and Future Perspectives

• The difficulties :
  • Reliability and reliability of data.
  • Data privacy and regulations.
  • Lack of adequate technology production.
• Future Perspectives :
  • Wider use of advanced analytical tools.
  • The rise of AI-powered trading platforms.
  • The harmony of digitalization in global trade.

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