Leveraging business data as a valuable asset is no longer a debated concept – it’s a broadly adopted, competitive undertaking that’s part and parcel to cloud modernization. Today, if there’s one thing that defines competitive advantage in the data analytics arena it’s streaming data platforms. Older approaches employing batch-only analytics, brittle ETL pipelines, and the latency they can introduce just don’t cut it anymore. Cloud-Modernized Analytics are poised to step in and take over.
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The world of data and analytics is evolving faster than ever before. Those that stay ahead of this change will be able to navigate the challenging economy and dominate the decade of data.
Data is driving tectonic shifts across our personal and professional lives, creating new opportunities for organizations - and new challenges. But which trends are truly transformative and which will fail to live up to the hype?
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Moving on-premises legacy data and analytics workloads to the cloud is unavoidable if you want to overcome infrastructural constraints, facilitate proactive analytics, and lower costs.
You need a service that enables seamless scalability for petabyte-scale data processing, interactive analytics, and machine learning. However, end-to-end, automated workload transformation and optimization on serverless services is not straightforward.
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Most databases are based on architectures that pre-date advances to modern hardware. This results in performance issues, the need to overprovision, and a high total cost of ownership. In this webinar, we will discuss the advances to modern server technology and take a deep dive into ScyllaDB’s shard-per-core architecture and our asynchronous engine, the Seastar framework.
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