Where is the All-Flash Data Center?

The all-flash data center was to solve all our problems. We’ve had all-flash arrays for ½ a decade. Where are the all-flash data centers? The problem is that performance and cost have been opposing forces in data storage systems for decades, especially in the initial all-flash era. Recent advancements in flash technology are finally breaking this tension and are enabling a new class of applications while driving costs down dramatically.
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Spotlight

OTHER ON-DEMAND WEBINARS

Using Data Exploration to Accelerate Traditional and Data Science Analytics Processes

Datameer

Modern analytics processes are less about creating dashboards and more about asking “why” questions. Business users and analysts need the ability to dig deeper to answer these questions—to get beyond dashboards and into the wealth of data organizations hold. View this TDWI webinar to learn how data exploration can speed time to insight. During this webinar, TDWI and Datameer will discuss: The role of visual data exploration in analytics cycles and where it can help streamline processes.
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Accelerating AI Adoption with Machine Learning Operations (MLOps)

Massive investments in data science teams and machine learning platforms have yet to yield results for most companies. The last mile for AI project success is the deployment and management of models in production requiring new technology and practices. This new area is called Machine Learning Operations or MLOps.
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Introduction to Einstein Bots for Developers

salesforce

Einstein Bots enable your customers to quickly and accurately interact with your company without waiting for a human agent to become available. Join us in this webinar as we talk about and show how Einstein Bots can be used to make your apps smarter without code, and how we can extend the functionality of Einstein Bots using Apex and external integrations.
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The 3 Things You Need to Become an AI-Driven Enterprise

Data Robot

As machine learning and artificial intelligence (AI) become must-have capabilities in every industry, organizations are realizing they need to become AI-driven enterprises in order to remain competitive. However, many companies hesitate to implement AI solutions because of three major concerns: finding the expertise required to build high-quality AIs from machine learning models, a lack of trust in “black box” decision-making, and prohibitively long machine learning project timelines that affect time to market.
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