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Published By: DATAVERSITY     Published Date: Jul 06, 2015
The growth of NoSQL data storage solutions have revolutionized the way enterprises are dealing with their data. The older, relational platforms are still being utilized by most organizations, while the implementation of varying NoSQL platforms including Key-Value, Wide Column, Document, Graph, and Hybrid data stores are increasing at faster rates than ever seen before. Such implementations are causing enterprises to revise their Data Management procedures across-the-board from governance to analytics, metadata management to software development, data modeling to regulation and compliance. The time-honored techniques for data modeling are being rewritten, reworked, and modified in a multitude of different ways, often wholly dependent on the NoSQL platform under development. The research report analyzes a 2015 DATAVERSITY® survey titled “Modeling NoSQL.” The survey examined a number of crucial issues within the NoSQL world today, with focus on data modeling in particular.
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DATAVERSITY
Published By: Denodo     Published Date: Feb 07, 2019
With the advent of big data and the proliferation of multiple information channels, organizations must store, discover, access, and share massive volumes of traditional and new data sources. Data virtualization transcends the limitations of traditional data integration techniques such as ETL by delivering a simplified, unified, and integrated view of trusted business data. Learn how you can: • Conquer siloed data in the enterprise • Integrate all data sources and types • Cope with regulatory requirements • Deliver big data solutions that work • Take the pain out of cloud adoption • Drive digital transformation
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Denodo
Published By: Databricks     Published Date: Sep 13, 2018
Learn how to get started with Apache Spark™ Apache Spark™’s ability to speed analytic applications by orders of magnitude, its versatility, and ease of use are quickly winning the market. With Spark’s appeal to developers, end users, and integrators to solve complex data problems at scale, it is now the most active open source project with the big data community. With rapid adoption by enterprises across a wide range of industries, Spark has been deployed at massive scale, collectively processing multiple petabytes of data on clusters of over 8,000 nodes. If you are a developer or data scientist interested in big data, learn how Spark may be the tool for you. Databricks is happy to present this ebook as a practical introduction to Spark. Download this ebook to learn: • Spark’s basic architecture • Why Spark is a popular choice for data analytics • What tools and features are available • How to get started right away through interactive sample code
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Databricks
Published By: Couchbase     Published Date: Jul 15, 2013
NoSQL database technology is increasingly chosen as viable alternative to relational databases, particularly for interactive web applications. Developers accustomed to the RDBMS structure and data models need to change their approach when transitioning to NoSQL. Download this white paper to learn about the main challenges that motivates the need for NoSQL, the differences between relational databases and distributed document-oriented databases, the key steps to perform document modeling in NoSQL databases, and how to handle concurrency, scaling and multiple-place updates in a non-relational database.
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white paper, database, nosql, couchbase
    
Couchbase
Published By: Embarcadero     Published Date: Jan 23, 2015
There are multiple considerations for collaborating on metadata within an organization, and you need a good metadata strategy to define and manage the right processes for a successful implementation. In this white paper, David Loshin describes how to enhance enterprise knowledge sharing by using collaborative metadata for structure, content, and semantics.
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data, data management, metadata, enterprise information management, data modeling, embarcadero
    
Embarcadero
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: Cloudant - an IBM Company     Published Date: Aug 01, 2015
The database you pick for your next web or mobile application matters now more than ever. Today’s applications are expected to run non-stop and must efficiently manage continuously growing amounts of transactional and multi-structured data in order to do so. This has caused NoSQL to grow from a buzzword to a serious consideration for every database, from small shops to the enterprise. Read this whitepaper to learn why NoSQL databases have become such a popular option, explore the various types available, and assess whether you should consider implementing a NoSQL solution for your next application.
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Cloudant - an IBM Company
Published By: Melissa Data     Published Date: Jan 18, 2018
Maintaining high quality data is essential for operational efficiency, meaningful analytics and good long-term customer relationships. But, when dealing with multiple sources of data, data quality becomes complex, so you need to know when you should build a custom data quality tools over canned solutions. To answer this question, it is important to understand the difference between rules-based data quality, where internal subject matter expertise is necessary – and active data quality, where different domain expertise and resources are required.
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Melissa Data
Published By: Experian     Published Date: May 17, 2016
Every year, Experian Data Quality conducts a study to look at the global trends in data quality. This year, research findings reveal how data practitioners are leveraging and managing data to generate actionable insight, and how proper data management is becoming an organization-wide imperative. This study polled more than 1,400 people across eight countries globally from a variety of roles and departments. Respondents were chosen based on their visibility into their orgazation's customer data management practices. Read through our research report to learn: - The changes in channel usage over the last 12 months - Expected changes in big data and data management initiatives - Multi-industry benchmarks, comparisons, and challenges in data quality - And more! Our annual global benchmark report takes a close look at the data quality and data management initiatives driving today's businesses. See where you line up and where you can improve.
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Experian
Published By: Finch Computing     Published Date: Apr 26, 2016
FinchDB is not just a database, not just an analytics engine and not just a search tool. It’s all three. All together. All in-memory. It’s a new, enabling platform technology built on an IP portfolio of 25 unique inventions, and suited for multiple high-volume, high-stakes use cases. While other big data solutions are answers-oriented, FinchDB enables users to ask better questions of their data. Because better questions must come before better answers.
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Finch Computing
Published By: AtomRain     Published Date: Nov 07, 2017
The world is more connected than ever before, and data relationships only continue to multiply. Yet enterprises still operate largely with an incomplete perspective caused by segmented, non-contextual and disconnected data silos. Connected data is the key to surviving, growing and thriving. However, a transformation across the entire enterprise won’t happen overnight, and each step must be measurable from both a business and technical perspective. Organizations need expert guidance to move more swiftly and avoid costly technical pitfalls in the new paradigm. This paper examines the journey to what we call, “The Connected Enterprise”.
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AtomRain
Published By: Wave Computing     Published Date: Jul 06, 2018
This paper argues a case for the use of coarse grained reconfigurable array (CGRA) architectures for the efficient acceleration of the data flow computations used in deep neural network training and inferencing. The paper discusses the problems with other parallel acceleration systems such as massively parallel processor arrays (MPPAs) and heterogeneous systems based on CUDA and OpenCL, and proposes that CGRAs with autonomous computing features deliver improved performance and computational efficiency. The machine learning compute appliance that Wave Computing is developing executes data flow graphs using multiple clock-less, CGRA-based System on Chips (SoCs) each containing 16,000 processing elements (PEs). This paper describes the tools needed for efficient compilation of data flow graphs to the CGRA architecture, and outlines Wave Computing’s WaveFlow software (SW) framework for the online mapping of models from popular workflows like Tensorflow, MXNet and Caffe.
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Wave Computing
Published By: graphgrid     Published Date: Oct 02, 2018
Whether it’s for a specific application, optimizing your existing operations, or innovating new customer services, graph databases are a powerful technology that turn accessing and analyzing your data into a competitive advantage. Graph databases resolve the Big Data limitations and free up data architects and developers to build amazing solutions that predict behaviors, enable data driven decisions and make insightful recommendations. Yet just as cars aren’t functional with only engines, graph databases require surrounding capabilities including ingesting multi-source data, building data models that are unique to your business needs, ease of data interaction and visualization, seamless co-existence with legacy systems, high performance search capabilities, and integration of data analysis applications. Collectively, this comprehensive data platform turns graph capabilities into tangible insights that drive your business forward.
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graphgrid
Published By: graphgrid     Published Date: Oct 02, 2018
Whether it’s for a specific application, optimizing your existing operations, or innovating new customer services, graph databases are a powerful technology that turn accessing and analyzing your data into a competitive advantage. Graph databases resolve the Big Data limitations and free up data architects and developers to build amazing solutions that predict behaviors, enable data driven decisions and make insightful recommendations. Yet just as cars aren’t functional with only engines, graph databases require surrounding capabilities including ingesting multi-source data, building data models that are unique to your business needs, ease of data interaction and visualization, seamless co-existence with legacy systems, high performance search capabilities, and integration of data analysis applications. Collectively, this comprehensive data platform turns graph capabilities into tangible insights that drive your business forward.
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graphgrid
Published By: MarkLogic     Published Date: Apr 01, 2013
Data virtualization solves the problem of consolidating critical data scattered across silos, providing a comprehensive, actionable view of data assets. Learn how MarkLogic presents a unified view of multi-structured data across organizational silos.
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data management
    
MarkLogic
Published By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
Accelerate Digital Transformation. Make data center infrastructure cloud-ready. Optimize storage across clouds and data centers.
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Hewlett Packard Enterprise
Published By: Dell SB     Published Date: Jan 24, 2019
Top 3 Reasons to Use a Multi-Display Setup
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Dell SB
Published By: Rackspace     Published Date: Feb 01, 2019
Nearly nine in 10 enterprises have adopted a multi-cloud strategy, according to the latest RightScale State of the Cloud Report, and these enterprises use eight different clouds, on average. Increasingly, their cloud of choice is a public cloud. Every public cloud, however, is different. GCP is rapidly gaining users among companies of all sizes. Today, GCP’s customers include large global brands like Disney, eBay, HSBC, The Home Depot, Schlumberger and Verizon, and smaller ones like gaming platform Smash.gg and the Rhode Island School of Design, one of the nation’s leading arts and design institutions. Whether GCP is a good fit for your company depends on a multitude of factors. To find out what these are and how Rackspace can help your business, download this whitepaper today.
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Rackspace
Published By: Lenovo - APAC     Published Date: Jan 23, 2019
For Japan’s largest medical equipment wholesaler, Mutoh, ensuring its 300,000 products reach hospitals, clinics and health-centres on time is an imperative. Someone’s life depends on it. Without IT that wouldn’t be possible. But Mutoh’s IT infrastructure was unable to keep pace with the demands of the business. Every time an order came in, Mutoh had to pull data from different systems across multiple servers which was time-consuming. It needed an IT infrastructure that was fast, high-performing, reliable, stable, and flexible. Mutoh turned to Lenovo’s hyperconverged infrastructure that helped the company achieve: • The ability to seamlessly extract data from different systems across multiple physical servers helped Mutoh respond to customer orders as quickly as possible, thereby saving lives • A modular hyperconverged solution allowed Mutoh to invest on a need basis, improving ROI and addressing spikes in customer demand
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lenovodcg, nutanix, hyperconvergedinfrastructure, hci
    
Lenovo - APAC
Published By: Lenovo - APAC     Published Date: Jan 23, 2019
For Japan’s largest medical equipment wholesaler, Mutoh, ensuring its 300,000 products reach hospitals, clinics and health-centres on time is an imperative. Someone’s life depends on it. Without IT that wouldn’t be possible. But Mutoh’s IT infrastructure was unable to keep pace with the demands of the business. Every time an order came in, Mutoh had to pull data from different systems across multiple servers which was time-consuming. It needed an IT infrastructure that was fast, high-performing, reliable, stable, and flexible. Mutoh turned to Lenovo’s hyperconverged infrastructure that helped the company achieve: • The ability to seamlessly extract data from different systems across multiple physical servers helped Mutoh respond to customer orders as quickly as possible, thereby saving lives • A modular hyperconverged solution allowed Mutoh to invest on a need basis, improving ROI and addressing spikes in customer demand
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lenovodcg, nutanix, hyperconvergedinfrastructure, hci
    
Lenovo - APAC
Published By: Lenovo - APAC     Published Date: Jan 23, 2019
For Japan’s largest medical equipment wholesaler, Mutoh, ensuring its 300,000 products reach hospitals, clinics and health-centres on time is an imperative. Someone’s life depends on it. Without IT that wouldn’t be possible. But Mutoh’s IT infrastructure was unable to keep pace with the demands of the business. Every time an order came in, Mutoh had to pull data from different systems across multiple servers which was time-consuming. It needed an IT infrastructure that was fast, high-performing, reliable, stable, and flexible. Mutoh turned to Lenovo’s hyperconverged infrastructure that helped the company achieve: • The ability to seamlessly extract data from different systems across multiple physical servers helped Mutoh respond to customer orders as quickly as possible, thereby saving lives • A modular hyperconverged solution allowed Mutoh to invest on a need basis, improving ROI and addressing spikes in customer demand
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lenovodcg, nutanix, hyperconvergedinfrastructure, hci
    
Lenovo - APAC
Published By: Mimecast     Published Date: Jan 17, 2019
Two-thirds of all internally generated email sent is from employees communicating within an organization*. Yet most IT organizations only focus on inbound email when it comes to protecting against cyber-attacks. In doing so, they ignore the serious risks posed by internal and outbound emails and the actions of two at risk groups of users - the compromised and careless employee. Mimecast Internal Email Protect extends the security capabilities of Targeted Threat Protection to provide advanced inside-the-perimeter defenses. Watch this on-demand webinar where Mimecast’s Chief Trust Officer, Marc French, and Cyber Security Strategist, Bob Adams discuss: The top things to do to optimize your Targeted Threat Protection implementation and prepare for addressing the threats on the inside. The multiple ways internal email threats start, and why human error nearly always plays a role. The scale and impact of attacks that spread via internal email. How to extend your current protection with Mim
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Mimecast
Published By: Black Duck Software     Published Date: May 18, 2010
In this webinar Black Duck Software (www.blackducksoftware.com), together with representatives of SAP, will review the benefits open source offers to development organizations, the management challenges it presents, and approaches for addressing those challenges.
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black duck software, open source, platform, sap, multi-source, code, source
    
Black Duck Software
Published By: Black Duck Software     Published Date: Oct 01, 2009
Over the past decade, a powerful new approach to development - open source software - has risen to prominence, dramatically increasing the opportunity to re-use existing software.
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black duck software, open source, platform, sap, multi-source, code, source, intellectual property
    
Black Duck Software
Published By: Black Duck Software     Published Date: Feb 17, 2009
"Agile" software development is an increasingly popular development process for producing software in a flexible and iterative manner that can deliver value to the enterprise faster, reduce project risk and allow adaptation to changes more quickly.
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black duck software, open source, platform, sap, multi-source, code, source, agile development
    
Black Duck Software
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