The Data transformation process must be a cultural movement within strategic and innovative businesses. Your long-term digital transformation strategy must have a systematic approach to be successful.
Priorities are changing, and companies are reexamining emerging technologies with a higher focus on digital initiatives as they develop new growth strategies
Enabling metrics within each instances of the AWS environment with the Elastic Network Adapters provides visibility into troubleshooting issues, right sizing activities, and benchmarking application performance.
Data In Motion
Transforming Data access within the organization is crucial for business leaders to make strategic decisions upon the most current information available. Enforcing encryption in transit, certificate / key management, and automated detection of unintended access must be implemented to safe guard intellectual property.
Businesses who develop a multi-cloud strategy are able to take advantage of different cloud services that perform best for specific tasks like data transfers, analytics, or compute resiliency. Embracing this strategy will also help the business achieve the maximum ROI for by taking advantage of pricing competition of the major cloud providers.
Data integration is one of the key benefits of a the data transformation process but can also impose a security risk to the organization. Raising the security posture across all IT assets is key to prevent, detect, respond, and remediate risks to corporate data. Protect your AWS accounts, workloads, and data with Amazon Guard Duty for intelligent threat detection.
Many of today’s innovative businesses are embracing machine learning technologies for medical diagnosis, image processing, and high-tech manufacturing for real time analytics. Amazon Kinesis makes the collection, process, and analyzation of data stream in real time.
AI services add intelligence to applications and workflows to help improve business outcomes. With AWS you can build AI powered applications without any machine learning expertise. Business metrics analysis, DevOps, code reviews, and abnormal machine behavior are just a few of the use cases for Amazon AI services.