Deliver Big Data and Databases as-a-Service on Kubernetes

Robin Systems, Inc

You need greater efficiency, agility, scalability, and cost-effectiveness from your IT infrastructure. Legacy storage solutions just aren’t cutting it anymore! What many IT Organizations don’t know is that there are many different solutions available to solve these IT challenges! The one thing that all businesses have in common is that they want and need IT solutions to make their lives easier, more efficient, and more affordable, particularly as digital transformation efforts take center stage. Converged, hyperconverged, composable, and other integrated platforms (collectively, integrated systems) all have the potential to accomplish these goals which can allow the IT organization to focus their efforts more on business outcomes rather than hardware.
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Spotlight

Oliver Spark, CEO & Founder of Sweet Analytics, shares the key benefits of Sweet Analytics.

OTHER ON-DEMAND WEBINARS

Everything Data Scientists Should Know About Organizing Data Lakes

simplilearn.com

The recent GDPR regulations have changed the way companies handle the data they collect and store, making it imperative for data scientists to explore innovative ways to crunch and catalog data while ensuring that the company adheres to these new rulings that seek to establish complete data security.Join Big Data Expert Ronald Van Loon, and Simplilearns Chief Product Officer Anand Narayanan in a live video chat to understand.
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High-Impact Analytics for Financial Services: Integration Updates to Salesforce Genie, Snowflake, and CRM Analytics

Learn how the unique relationship between Salesforce Genie, Snowflake, and CRM Analytics is creating new ways for financial services firms to realize the value of customer data. Join us as industry leaders showcase the different real-time data integration options and discuss how customers are leveraging these platforms to achieve success today.
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Automated Data and Analytics Workload Modernization

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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Building a Modern Operational Data Warehouse

tdwi.org

With data coming from so many different sources nowadays (both old and new, both internal and external), it is inevitable that data will arrive in many different structures, schema, and formats, with other variables for latency, concurrency, and requirements for storage and processing. When data types are extremely diverse and combined, we now call it “hybrid data.” This usually drives users to deploy many types of databases and different platforms to capture, store, process, and analyze the data, which in turn results in hybrid data management architectures.
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