Choosing the Right Database for Time Series Data

MemSQL

In this webinar, MemSQL Product Marketing Manager Mike Boyarski describes the growth in popularity of time series data and talks about the best options for a time series database, including a live Q&A. You can view the webinar and download the slides here. Here at MemSQL, we’ve had a lot of interest in our blog posts on time series data and choosing a time series database, as well as our O’Reilly time series ebook download. However, this webinar does a particularly good job of explaining what you would want in a time series database, and how that fits with MemSQL. We encourage you to read this blog post, then view the webinar.
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Spotlight

Data modeling makes it easier for developers, data architects, business analysts, and other stakeholders to view and understand relationships among the data in a database or data warehouse. Benefits of data modeling helps companies take fast data-driven decisions and enhance the business processes at a higher rate.

OTHER ON-DEMAND WEBINARS

Data Science for Spreadsheet Users

DataCamp

In this webinar, DataCamp Account Executive Chris Cardillo will challenge anyone spending their days in and out of spreadsheets to pick up a coding language. He’ll cover the tangible benefits of incorporating coding into an everyday workflow, as well as examples of where coding enhances or replaces work done in spreadsheets. Finally, he’ll cover some R language equivalents for spreadsheet techniques, and where to get started when you’re ready to take the first step.
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Empowering Data Scientists with MLOps

Why is it that 80% of enterprises fail to scale AI? Data scientists face operational, collaborative and infrastructure complexities at each step of the ML lifecycle. MLOps practices have the ability to solve many ML operational concerns such as project deployment, testing, serving and monitoring. In this webinar, Yochay Ettun, CEO and Co-founder of cnvrg.io will discuss the ways that MLOps solutions empower data scientists to successfully operationalize ML by applying DevOps principles to the ML lifecycle.
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Modernizing Metadata

tdwi.org

Metadata is more relevant than ever. It continues to be a powerful enabler for high-value data-driven business activities across operations, analytics, and compliance. However, to maintain this relevance, metadata management must deal with the increasing complexity of today’s business use cases and hybrid data environments. Metadata management is notoriously manual which makes it slow in development and error-prone in maintenance. Metadata management needs better tool automation. Metadata management is typically siloed due to users managing metadata per tool or platform. Metadata management needs a unified solution that is suited to sharing, reuse, governance, and comprehensive views of distributed data.
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Bridge the Cloud Divide with Pure Storage Cloud Data Services

BytesTechnology

Pure Storage have recently launched their Cloud Data Services - a new set of capabilities allowing you to easily embrace a hybrid cloud architecture and ditch the cloud divide. Where once private and public cloud data storage operated in separate worlds, Pure’s Cloud Data Services now bring on-premises functionality to the cloud. Plainly put, all the features, benefits, and advantages of running Pure FlashArray in your datacentre, will soon be available in AWS – with zero compromise.
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Spotlight

Data modeling makes it easier for developers, data architects, business analysts, and other stakeholders to view and understand relationships among the data in a database or data warehouse. Benefits of data modeling helps companies take fast data-driven decisions and enhance the business processes at a higher rate.

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