25/09 Webinar. Enterprise Data and AWS AI Services. Examples of use

AWS AI Services for working with enterprise data

Date: September 25, 2024 | Time: 11:00 (GMT+5) | Format: online.

Webinar language: Russian

Webinar registration

The webinar will cover the following issues:

• Generative AI perspectives for business
• Latest AWS services based on Generative AI 
• Key aspects of enterprise data and AI interaction
• Examples of analyzing enterprise data using AWS services.

Webinar registration

Key aspects of enterprise data and AI interoperability in AWS services:

Companies are using AWS Generative AI for such tasks:

Big data analysis

Big data processing: AI is able to process the huge amounts of data that accumulate in corporate systems and extract useful information from them.

Identifying patterns: Using machine learning algorithms, AI can find hidden patterns and trends that may go undetected by traditional analysis.

Forecasting

Market Forecasting: AI can analyze historical data and market trends to create predictions about market developments, product demand, or changes in consumer behavior.

Financial Forecasting: Using AI to analyze financial data allows you to predict a company's possible financial results, identify risks and investment opportunities.

Business process optimization

Inventory management: AI can analyze inventory, sales, and demand data to optimize inventory management, reduce costs, and prevent product shortages or surpluses.

Logistics and supply chain: AI data analysis can optimize delivery routes, warehouse inventory management, and overall supply chain efficiency.

Personalizing customer experience

Customer behavior analysis: AI can collect and analyze customer behavior data to create personalized offers, recommendations, and marketing campaigns.

Customer Feedback Processing: Using Natural Language Processing (NLP), AI can analyze text-based customer feedback, identify key issues, and assess customer satisfaction.

Cybersecurity

Threat detection: AI can analyze network data and other digital signals to identify anomalies and potential threats, helping to prevent cyberattacks.

Incident response automation: AI can automatically respond to specific types of cyber threats, reducing response times and increasing a company's defenses.

Reduced costs

Automation of routine tasks: AI can perform routine tasks such as document processing or data entry, reducing manual labor costs and improving accuracy.

Resource optimization: Data analysis can help optimize the use of resources, such as energy or materials, which also reduces costs.

Decision-making support

Recommender systems: AI can provide managers with recommendations based on data analysis, helping them make more informed decisions.

Data visualization: AI can automatically create interactive reports and visualizations to help better understand complex data and simplify decision-making.

Webinar registration

Softprom — Advanced Consulting Partner in the Amazon Web Services network. Has MAP (Migration Acceleration Program) status of AWS partner, performs projects on infrastructure migration to the cloud for Enterprise-level companies.