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					 Article ArticleArtificial intelligence data storage planning best practicesAI storage planning is similar to the storage planning you're used to: Consider capacity, IOPS and reliability requirements for source data and the application's database. Read Now 
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					 Article Article2019 IT focus: Storage architecture for big data analyticsTop storage technologists and analysts predict IT organizations will focus on revamping their storage architectures to make better use of data for analytics, AI and IoT in 2019. Read Now 
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					 Article ArticlePerfect AI-defined infrastructure by analyzing your data centerBefore implementing AI, evaluate your IT team and data storage center. Experts explain the fundamental elements of data storage required to tailor an AI-defined infrastructure. Read Now 
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					 Article ArticleCloud-based predictive analytics seeing wider adoptionA predictive analytics tool can give your storage strategy a boost by addressing storage issues before they even occur. What should you look for in a predictive analytics product? Read Now 
Editor's note
Storage is getting progressively smarter as analytics capabilities are increasingly integrated into arrays and other parts of the storage layer. Predictive storage analytics, AI and machine learning are coming together to enhance and optimize storage infrastructure and proactively address problems.
Behind the move to more intelligent storage is the increasing use of all-flash arrays (AFAs) and hybrid and hyper-converged infrastructure, along with the greater demand for real-time data on storage capacity and performance.
"Storage is no longer a separate slice of the data center technology stack that you can intelligently manage or analyze in isolation. Looking at larger slices of the stack requires the use of more sophisticated analytical approaches over bigger data," said Mike Matchett, analyst at Small World Big Data.
Storage vendors are gathering vast amounts of data from their customers and applying data mining, analytical queries and predictive modeling to these aggregated data sets to forecast trends. They're feeding the resulting analysis back to their customers to help them plan infrastructure, reduce overhead and proactively address problems before they happen.
AI and machine learning have been added into the predictive storage analytics mix, to continually improve data collection tools and data analysis. The end result is self-healing storage infrastructures that autonomously identify and resolve issues, providing better capacity management, reduced downtime, and increased application availability, performance and productivity.
Below, we've pulled together insight into the current state of storage analytics, along with a look at how some enterprises are using new techniques and technology to make their storage infrastructure smarter. We also take a look at the roles AI and machine learning are playing. And if you're curious about the vendors that are active in this market and what products are available, we've included the latest updates on the vendors and the products they're offering.
1Guidance and use cases
Learn how the use of all-flash arrays, predictive storage analytics, AI and machine learning are combining to make storage faster and smarter.
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							AI for storage management gets realAI for storage is popping up everywhere, though much of what we're seeing is the automation of routine tasks. Discover what vendors are doing to use AI more creatively. Read Now 
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							Cloud-based predictive storage analytics takes offPredictive analytics tools proactively address storage issues. Find out what to look for in these products. Read Now 
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							AFAs take on challenges of big data storageThe latest generation of AFA storage provides what's needed to support petabyte-scale big data analytics workloads. Read Now 
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							5 predictive storage analytics features you'll want to watch forPredictive storage analytics tools are becoming standard equipment in the enterprise. Get to know the features you'll need, how they work and the benefits they provide. Read Now 
2The latest insight and strategy
See how AI is being integrated into storage technology and providing unique insight into capacity and performance.
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							2019 IT focus: Storage architecture for big data analyticsTop storage technologists and analysts predict IT organizations will focus on revamping their storage architectures to make better use of data for analytics, AI and IoT in 2019. Read Now 
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							AI and big data comparedHow AI can help synthesize and analyze the large volumes of information provided by big data initiatives. Read Now 
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							Artificial intelligence data storage planning best practicesAI storage planning is similar to the storage planning you're used to: Consider capacity, IOPS and reliability requirements for source data and the application's database. Read Now 
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							NetApp jumps into AI storageVendor packages its AFAs with Nvidia GPUs to meet growing demand for AI storage. Read Now 
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							Pure Storage unveils AI-based storageAll-flash vendor and high-performance GPU specialist Nvidia rolled out a preconfigured storage stack to accelerate data-intensive analytics at scale. Read Now 
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							Ultrathin memory storage could improve AI and analytics applications3D chips using atomristors will have a memory architecture with 3D connections similar to those found in the human brain. Read Now 
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							Perfect AI-defined infrastructure by analyzing your data centerBefore implementing AI, evaluate your IT team and data storage center. Experts explain the fundamental elements of data storage required to tailor an AI-defined infrastructure. Read Now 
3The predictive analytics and AI market
Find out which vendors are offering intelligent storage products and how those products might help your organization.
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							HPE InfoSight to add support for partners' storage productsHPE GM of storage Milan Shetti outlines plans to add support for partners' storage products in its InfoSight predictive analytics platform and talks up its AI operations-centric strategy. Read Now 
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							Hitachi Vantara explains where it's heading with AI and storageVendor updates Hitachi Storage Virtual Operating System and Virtual Storage Platform to address data mobility among data centers, edge environments and the cloud. Read Now 
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							Veritas acquires Aptare for storage analyticsVeritas acquired storage monitoring software vendor Aptare on the advice of common customers and will integrate its features in NetBackup and other data protection applications. Read Now 
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							Violin Systems AFA arrays incorporate predictive storage analyticsVendor's XVS line streams telemetry data to Violin's cloud system using the Symphony flash management console. Read Now 
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							Hitachi Vantara's analytics for storage enhance visual mappingUpgrade extends the role AI plays in storage analytics for data protection and hybrid cloud environments. Read Now 
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							HPE InfoSight automates 3PAR customer supportHPE added automated support resolution capabilities to the InfoSight predictive analytics on its 3PAR arrays. Read Now 
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							Vexata capitalizes on NVMe flash storage to take on analyticsAFA upgrade targets need for fast storage in cognitive computing. Read Now 
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							Predictive analytics for storage: Benefits and product optionsThe advantages of using predictive analytics in storage include less downtime and better resource utilization. It's no wonder more storage vendors are making it an option. Read Now 
4A list of essential definitions
Learn some of the key terms regarding predictive storage analytics, AI and machine learning and test your knowledge by taking our short quiz.