Cloud analytics
01 - The challenge
01
The challenge
Today, more and more companies are turning to predictive analytics and artificial intelligence to turn available information and data into business advantage. However, launching a data and AI project with traditional tools can be a time- and cost-intensive process: it can require a large investment to procure GPU-powered servers, supporting software, build the development environment, and then secure and manage this productive environment with appropriate security and redundancy.
02 - The solution
02
The solution
Areas where AWS can help:
- Recommendations: customise your shopping experience
- Forecasting: create accurate forecasting models
- Image and video analysis: add image and video analysis to your applications
- Document analysis: automatically extract text and data from millions of documents in just a few hours
- Voice: converts text into lifelike speech, so you can add voice to your applications
- Translation: increase your reach to a larger audience with efficient and cost-effective translation
- Fraud prevention: identify potentially fraudulent online activities based on technology used by Amazon.com
Other solutions
24/7 Managed Services
Although AWS platform offers a wide range of managed services, the level of responsibility for operating each of the services varies, based on the AWS Shared Responsibility model.
Migration Acceleration Program
The use of cloud computing and digitalization is a prerequisite for improving the efficiency of business operations, the ability to adapt to market changes, the development of elasticity agility and optimal cost structures.
SAP on AWS
SAP systems play a key role in the everyday processes of many companies worldwide. They require special hardware and extremely high availability being business-critical systems. With the introduction of the SAP HANA database and the retirement of SAP support for alternative databases, it will be essential for hundreds of companies to switch platforms in the next 5-10 years. However, this can be a risky project in a traditional environment because of the magnitude of hardware estimation, acquisition, and lifecycle tracking.