unstructured data

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Published By: Couchbase     Published Date: Dec 04, 2014
Interactive applications have changed dramatically over the last 15 years. In the late ‘90s, large web companies emerged with dramatic increases in scale on many dimensions: · The number of concurrent users skyrocketed as applications increasingly became accessible · via the web (and later on mobile devices). · The amount of data collected and processed soared as it became easier and increasingly · valuable to capture all kinds of data. · The amount of unstructured or semi-structured data exploded and its use became integral · to the value and richness of applications. Dealing with these issues was more and more difficult using relational database technology. The key reason is that relational databases are essentially architected to run a single machine and use a rigid, schema-based approach to modeling data. Google, Amazon, Facebook, and LinkedIn were among the first companies to discover the serious limitations of relational database technology for supporting these new application requirements. Commercial alternatives didn’t exist, so they invented new data management approaches themselves. Their pioneering work generated tremendous interest because a growing number of companies faced similar problems. Open source NoSQL database projects formed to leverage the work of the pioneers, and commercial companies associated with these projects soon followed. Today, the use of NoSQL technology is rising rapidly among Internet companies and the enterprise. It’s increasingly considered a viable alternative to relational databases, especially as more organizations recognize that operating at scale is more effectively achieved running on clusters of standard, commodity servers, and a schema-less data model is often a better approach for handling the variety and type of data most often captured and processed today.
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database, nosql, data, data management, white paper, why nosql, couchbase
    
Couchbase
Published By: MarkLogic     Published Date: Jun 17, 2015
Modern enterprises face increasing pressure to deliver business value through technological innovation that leverages all available data. At the same time, those enterprises need to reduce expenses to stay competitive, deliver results faster to respond to market demands, use real-time analytics so users can make informed decisions, and develop new applications with enhanced developer productivity. All of these factors put big data at the top of the agenda. Unfortunately, the promise of big data has often failed to deliver. With the growing volumes of unstructured and multi-structured data flooding into our data centers, the relational databases that enterprises have relied on for the last 40-years are now too limiting and inflexible. New-generation NoSQL (“Not Only SQL”) databases have gained popularity because they are ideally suited to deal with the volume, velocity, and variety of data that businesses and governments handle today.
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data, data management, databse, marklogic, column store, wide column store, nosql
    
MarkLogic
Published By: Skytree     Published Date: Nov 23, 2014
Critical business information is often in the form of unstructured and semi-structured data that can be hard or impossible to interpret with legacy systems. In this brief, discover how you can use machine learning to analyze both unstructured text data and semi- structured log data, providing you with the insights needed to achieve your business goals.
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log data, machine learning, natural language, nlp, natural language processing, skytree, unstructured data, semi-structured data, data analysis
    
Skytree
Published By: Expert System     Published Date: Mar 19, 2015
Establishing context and knowledge capture In today’s knowledge-infused world, it is vitally important for organizations of any size to deploy an intuitive knowledge platform that enables delivery of the right information at the right time, in a way that is useful and helpful. Semantic technology processes content for meaning, allowing for the ability to understand words in context: it allows for better content processing and interpretation, therefore enabling content organization and navigation, which in turn increases findability.
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enterprise data management, unstructured data, semantic technology, expert system
    
Expert System
Published By: DATAVERSITY     Published Date: Feb 27, 2013
In its most basic definition, unstructured data simply means any form of data that does not easily fit into a relational model or a set of database tables.
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white paper, dataversity, unstructured data, enterprise data management, data, data management
    
DATAVERSITY
Published By: MarkLogic     Published Date: Jun 16, 2013
The primary issue discussed within this paper boils down to two disparate database reliability models: ACID vs BASE. The first (ACID) has been around for some 30+ years, is a proven industry standard for SQL-centric and other relational databases, and works remarkably well in the older, yet still extant, world of vertical scaling. The second (BASE) has only recently gained popularity over the past 10 years or so, especially with the rise of social networking, Big Data, NoSQL, and other leviathans in the new world of Data Management. BASE requirements rose out of a need for ever-expanding horizontally scaled distributed networks, with non-relational data stores, and the real-time availability constraints of web-based transaction processing. While there are now more crossovers and negotiations between the two models, they essentially represent two competing groups, with Brewer’s CAP Theorem acting as the referee in the middle forcing tough decisions on each team.
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data, data management, unstructured data, nosql, database, acid, base, database transactioning
    
MarkLogic
Published By: Ted Hills     Published Date: Mar 29, 2016
NoSQL database management systems give us the opportunity to store our data according to more than one data storage model, but our entity-relationship data modeling notations are stuck in SQL land. Is there any need to model schema-less databases, and is it even possible? In this short white paper, Ted Hills examines these questions in light of a recent paper from MarkLogic on the hybrid data model. Ted Hills has been active in the Information Technology industry since 1975. At LexisNexis, Ted co-leads the work of establishing enterprise data architecture standards and governance processes, working with data models and business and data definitions for both structured and unstructured data. His book, NoSQL and SQL Data Modeling, was recently released by Technics Publications (http://technicspub.com).
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Ted Hills
Published By: MarkLogic     Published Date: Mar 29, 2018
Real World Evidence (RWE) requires the correlation of complex, frequently changing, unstructured data. To the enterprise architect, that means extracting value from data that doesn't neatly fit solutions. In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that is required to be successful with RWE. It is for this reason that leading life science organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic.
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data, integration, volume, optimization, architect, enterprise
    
MarkLogic
Published By: Attivio     Published Date: Aug 20, 2010
With the explosion of unstructured content, the data warehouse is under siege. In this paper, Dr. Barry Devlin discusses data and content as two ends of a continuum, and explores the depth of integration required for meaningful business value.
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attivio, data warehouse, unified information, data, content, unstructured content, integration, clob, blob, business intelligence, database development, data quality, data warehousing
    
Attivio
Published By: SAP     Published Date: Feb 03, 2017
The SAP HANA platform provides a powerful unified foundation for storing, processing, and analyzing structured and unstructured data. It funs on a single, in-memory database, eliminating data redundancy and speeding up the time for information research and analysis.
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SAP
Published By: Dell EMC     Published Date: May 23, 2017
The rapid growth of unstructured data poses significant challenges to store, manage, secure and protect data across virtually every industry segment. You need a way to manage your data: simply, securely and cost-effectively.
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Dell EMC
Published By: Amazon Web Services     Published Date: Dec 15, 2017
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time. AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance. In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences. Join this webinar to learn: How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development. How AWS supports BI solutions f
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Amazon Web Services
Published By: CrowdStrike     Published Date: May 10, 2018
One of the biggest challenges to effectively stopping breaches lies in sifting through vast amounts of data to find the proverbial “needle in the haystack” – the subtle clues that indicate an attack is imminent or underway. As modern computer systems generate billions of events daily, the amount of data to analyze can reach petabytes. Compounding the problem, the data is often unstructured, discrete and disconnected. As a result, organizations struggle to determine how individual events may be connected to signal an impending attack. In this context, detecting attacks is often difficult, and sometimes impossible. This white paper describes how CrowdStrike solved this challenge by building its own graph data model – the CrowdStrike Threat Graph? – to collect and analyze extremely large volumes of security-related data, and ultimately, to stop breaches. This revolutionary approach applies massive graph-based technologies, similar to the ones developed by Facebook and Google, to detect k
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CrowdStrike
Published By: IBM APAC     Published Date: Nov 22, 2017
It is imperative that organizations start looking now for smarter solutions to the problems associated with unstructured data. There are many issues related to unstructured data that need to be readily addressed such as storage, discovery, organization, tagging and deduplication. One of the most important issues related to unstructured data is finding and discovering key business insights as quickly as possible, preferably in near real time, to gain a significant competitive advantage.
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storage, discovery, organization, tagging, deduplication, competitive, advantage
    
IBM APAC
Published By: Dell EMC     Published Date: Oct 08, 2015
Download this whitepaper to learn more about how to capture, analyze and manage a tidal wave of structured and unstructured data, turn this data into operational intelligence, And how to overcome the limitations of databases and data management tools that weren’t designed for a world of big data with Dell.
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Dell EMC
Published By: SAS     Published Date: Apr 20, 2015
This paper explores how organizations are leveraging unstructured data—and what they must avoid.
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SAS
Published By: Cleversafe     Published Date: Dec 07, 2012
Dispersed Storage is an innovative approach for cost-effectively storing large volumes of unstructured data while ensuring security, availability and reliability.
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dispersed, storage, unstructured, availability, reliability, large volumes, it management, business technology, data center
    
Cleversafe
Published By: MarkLogic     Published Date: Aug 31, 2017
With the proliferation of IT infrastructure and the rapid rise of unstructured data, navigating the complexities of complying with the EU Regulation MiFID II can be overwhelming. But the first steps to compliance involve addressing your data management challenges head on.
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MarkLogic
Published By: Dell EMC     Published Date: Aug 22, 2017
Dell EMC Isilon® scale-out NAS is the ideal platform to store, manage, protect and analyze your unstructured data. Isilon is the only platform that scales capacity and performance in minutes – allowing you to infinitely consolidate unstructured data, cut costs, and gain new levels of agility and insight to accelerate your business.
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Dell EMC
Published By: Dell EMC     Published Date: Aug 22, 2017
This Lab Validation Report documents the results of recent hands-on testing of Dell EMC Isilon All-Flash storage. Testing focused on the platform’s performance and scalability and how it enables organizations to support more applications and workloads with flash based on their ever-increasing volumes of unstructured data.
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Dell EMC
Published By: Dell EMC     Published Date: Aug 22, 2017
Identifying the benefits, costs, and risks associated with an Isilon implementation, Forrester interviewed several customers with experience using Isilon. Dell EMC Isilon is a scale-out NAS platform that enables organizations to store, manage, and analyze unstructured data. Isilon clusters are composed of different node types that can scale up to 68 petabytes (PB) in a single cluster while maintaining management simplicity. Isilon clusters can also scale to edge locations and the cloud
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Dell EMC
Published By: Dell EMC     Published Date: Aug 22, 2017
GARTNER HAS NAMED DELL EMC AS A LEADER FOR DISTRIBUTED FILE SYSTEMS AND OBJECT STORAGE. This report evaluates Distributed File and Object Storage vendors that help customers deal with the rapid growth in unstructured data. Isilon, the industry leader in scale-out NAS storage, and Dell EMC Elastic Cloud Storage (ECS), were both recognized as leaders in this Gartner report. We believe this recognition demonstrates our industry-leading capabilities to help prepare our customers for their digital future.
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Dell EMC
Published By: Dell EMC     Published Date: Aug 22, 2017
Dell EMC Isilon, the #1 Scale-Out NAS platform, continues to transform the way organizations are deploying, protecting and managing their fast growing unstructured data. This session by Eric Seidman, Senior Manager, Product Marketing, Dell EMC will introduce attendees to the new generation of Isilon Scale-Out NAS family. Also covered will be a deep dive into the new Isilon architecture and a closer look at the six new Isilon systems – powered by the new OneFS 8.1 – which were announced at Dell EMC World 2017. Attend this session to learn how Isilon’s latest enhancements can revolutionize your business.
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Dell EMC
Published By: Pure Storage     Published Date: Nov 02, 2017
The tremendous growth of unstructured data is creating huge opportunities for organizations. But it is also creating significant challenges for the storage infrastructure. Many application environments that have the potential to maximize unstructured data have been restricted by the limitations of legacy storage systems. For the past several years—at least—users have expressed a need for storage solutions that can deliver extreme performance along with simple manageability, density, high availability and cost efficiency.
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high performance, tco, multi protocol, management simplicity, the blade, elasticity software, performance, capacity
    
Pure Storage
Published By: SAP EMEA Global     Published Date: Nov 22, 2017
As more and more data pours into the office of the CFO, experts say, minimizing its complexity and maximizing its usefulness becomes critical. “The amount of data is phenomenal,” says Mr. Whitehead of Airbus Defence and Space, “but what’s worse is the lack of harmonization. Unstructured data is what kills you. The key for me is how to have clear data in a usable and consistent form, which can be turned into succinct information the business can look at, understand where the value chain is, and make decisions.”
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finance, function, strategic, growth, initiatives, automation, efficiency, core, finance, processes
    
SAP EMEA Global
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