Unleashing Severe Data Consumption for Revolutionary Understandings
In today's data-driven world, businesses are grappling with the challenge of extracting smart insights from the vast amounts of data they collect. However, the advent of modern cloud-native data platforms promises to change this narrative.
Miles Ward, the CTO of SADA, an Insight company and a leading Google Cloud Partner, emphasizes the transformative power of these platforms. They offer significant benefits in terms of speed, scale, and enabling new ways of operating by leveraging cloud elasticity, automation, and integrated advanced features.
Firstly, cloud-native platforms enable much faster deployment and time to value. Businesses can now deploy solutions within hours rather than the traditional months, thanks to their rapid time to market and continuous integration/continuous delivery (CI/CD) processes. This rapid deployment supports increased development productivity and responsiveness.
Secondly, these platforms inherently support automatic scaling of compute and storage resources according to workload demands. This feature ensures efficient cost management by allowing businesses to pay only for what they use, from gigabytes to petabytes. The global footprint of cloud providers also ensures seamless scaling to support geographically distributed operations while maintaining reliability and redundancy.
Thirdly, modern cloud-native data platforms enable new ways of operating. They foster innovation and resilience through built-in AI and machine learning capabilities, enhanced collaboration across distributed teams, and governance improvements such as risk mitigation and security controls integrated with DevSecOps workflows. These aspects support business agility, improve customer experiences, and allow organizations to adopt proactive security postures efficiently.
Architecting these platforms for parallelism is crucial. Prioritizing design for parallelism often means rethinking old habits like Extract, Transform, Load (ETL) and embracing Extract, Load, Transform (ELT) and using data formats built for parallel reads. This approach allows these platforms to chew through massive datasets using incredible parallel processing power, a feat that legacy data systems often struggle with due to their inability to handle the current data influx.
Moreover, as businesses open up access to vast data pools, it is essential to implement rock-solid data governance. This includes addressing access control, security, privacy controls, data handling policies, compliance, and responsible use in a more open data environment.
Migrating huge, complex workloads to these modern platforms can result in immensely faster query speeds. When architected right, leveraging cloud elasticity and optimized processing, cloud data analytics costs can drop by over 90% compared to older setups.
In essence, the benefits of modern cloud-native data platforms include rapid and flexible scalability, accelerated insights and delivery speed, cost effectiveness, AI-driven innovation, enhanced collaboration, and improved governance and security that enable businesses to operate more dynamically and securely in a cloud environment.
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- Miles Ward, an expert in data-and-cloud-computing technology, asserts that cloud-native platforms, such as those offered by Google Cloud, provide businesses with speed, scale, and new ways of operating, particularly by enabling rapid deployment, automatic scaling, increased development productivity, and fostering innovation.
- In the data-driven world where businesses collect vast amounts of data, the deployment of modern cloud-native data platforms can lead to immense benefits, including reduced costs by over 90%, accelerated insights, and more dynamic and secure business operations, as emphasized by Miles Ward, the CTO of SADA.
