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Published By: Amazon Web Services     Published Date: Jul 25, 2018
What is a Data Lake? Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.
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Amazon Web Services
Published By: MarkLogic     Published Date: Aug 31, 2017
With MiFID II regulations demanding increased pre and post-trade transparency for consumers, investment banks are in a race against the clock to demonstrate compliance across a dizzying array of data sources, systems and schemas before January 2018.
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MarkLogic
Published By: Attunity     Published Date: Feb 12, 2019
Read this technical whitepaper to learn how data architects and DBAs can avoid the struggle of complex scripting for Kafka in modern data environments. You’ll also gain tips on how to avoid the time-consuming hassle of manually configuring data producers and data type conversions. Specifically, this paper will guide you on how to overcome these challenges by leveraging innovative technology such as Attunity Replicate. The solution can easily integrate source metadata and schema changes for automated configuration real-time data feeds and best practices.
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data streaming, kafka, metadata integration, metadata, data streaming, apache kafka, data integration, data analytics
    
Attunity
Published By: Oracle     Published Date: Mar 09, 2017
DANS CE LIVRE BLANC, IDC ANALYSE LES DIFFICULTES INHERENTES AUX SCHEMAS DE SAUVEGARDE TRADITIONNELS ET LES DYNAMIQUES MOUVANTES DES STRATEGIES DE PROTECTION DES DONNEES.
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Oracle
Published By: Stratoscale     Published Date: Feb 01, 2019
This eBook offers a practical hands-on guide to analyzing and mitigating the risks of migrating to PostgreSQL. With the ongoing shift towards open-source database solutions, it’s no surprise that PostgreSQL is the fastest growing database. While it’s tempting to simply compare the licensing costs of proprietary systems against that of open source, it is both a misleading and incorrect approach when evaluating the potential for return on investment of a database technology migration. A key decision criteria for adopting any technology is whether it can support requirements for existing applications while also fitting into longer term strategies and needs. The first section of this eBook provides a detailed analysis of all aspects of migrating from legacy and commercial solutions to PostgreSQL: ? Schema and code migration ? Data migration ? Application code migration ? Testing and evaluation
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Stratoscale
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
MongoDB is an open-source, document database designed with both scalability and developer agility in mind. MongoDB bridges the gap between key-value stores, which are fast and scalable, and relational databases, which have rich functionality. Instead of storing data in rows and columns as one would with a relational database, MongoDB stores JSON documents with dynamic schemas. Customers should consider three primary factors when evaluating databases: technological fit, cost, and topline implications. MongoDB's flexible and scalable data model, robust feature set, and high-performance, high-availability architecture make it suitable for a wide range of database use cases. Given that in many cases relational databases may also be a technological fit, it is helpful to consider the relative costs of each solution when evaluating which database to adopt.
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total, cost, ownership, comparison, mongodb, oracle
    
AstuteIT_ABM_EMEA
Published By: AWS     Published Date: Nov 15, 2018
Businesses are generating staggering amounts of data—and extracting the most value from this information is paramount. Amazon Redshift provides organizations what they’re looking for: Affordability and flexibility combined with a powerful feature set. Download our solution overview covering some of the best practices on loading data and making the most of Amazon Redshift, including: • Loading data for faster results • Querying data for gaining actionable insights • Creating a schema to forgo complicated queries, saving time
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AWS
Published By: AWS     Published Date: Nov 02, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it’s readily available to be categorized, processed, analyzed, and consumed by diverse groups within an organization. Since data - structured and unstructured - can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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AWS
Published By: Cohesity     Published Date: Aug 09, 2019
In a context of mass data fragmentation on-premises and in the cloud, organizations now struggle with the compounded complexities brought about by modern workloads such as containers, NoSQL/NewSQL databases, and SaaS applications. These new workloads are turning traditional backup and recovery approaches on their head—in particular, in Microsoft Office 365 deployments for which new backup, recovery, and data management schemas must be deployed.
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Cohesity
Published By: IBM     Published Date: May 04, 2009
Intel faces a familiar challenge: do more with less. With compute capacity growing exponentially and chip size expectation shrinking, the new 5500 series delivers on both fronts. This white paper delivers test results that show increased performance and speed along with greater efficiency.
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ibm, express seller, virtualization intel, xeon, processor, 5500, bladecenter, system x
    
IBM
Published By: Quark Software     Published Date: Mar 19, 2015
For decades technical writers have reaped the benefits of XML to lower the cost and effort associated with creating, managing and reusing content across multiple output formats. Now, with the introduction of Smart Content, business users and subject matter experts can easily adopt XML in order to keep up with consumer demand for high-value communication. Download the free eBook The Beginner’s Guide to Smart Content and discover: • What is Smart Content? • A Brief Primer on Publishing Processes • The Cost of Smart Content • Who Else Is Using XML for Document Production? • What’s Wrong with XML? • Smart Content Details • 12 Reasons to Adopt Smart Content
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xml schema, xml tool, xml authoring, structured authoring, structured content, dynamic publishing, enterprise publishing, automated publishing
    
Quark Software
Published By: Microsoft Azure     Published Date: Apr 11, 2018
Developing for and in the cloud has never been more dependent on data. Flexibility, performance, security—your applications need a database architecture that matches the innovation of your ideas. Industry analyst Ovum explored how Azure Cosmos DB is positioned to be the flagship database of internet-based products and services, and concluded that Azure Cosmos DB “is the first to open up [cloud] architecture to data that is not restricted by any specific schema, and it is among the most flexible when it comes to specifying consistency.” From security and fraud detection to consumer and industrial IoT, to personalized e-commerce and social and gaming networks, to smart utilities and advanced analytics, Azure Cosmos DB is how Microsoft is structuring the database for the age of cloud. Read the full report to learn how a globally distributed, multi-model data service can support your business objectives. Fill out the short form above to download the free research paper.
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Microsoft Azure
Published By: AWS     Published Date: Oct 26, 2018
Today’s organisations are tasked with analysing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organisations are finding that in order to deliver analytic insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store enormous amounts of data in a central location, so it’s readily available to be categorised, processed, analysed, and consumed by diverse groups within an organisation? Since data—structured and unstructured—can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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data, lake, amazon, web, services, aws
    
AWS
Published By: IBM     Published Date: Aug 24, 2009
Making changes to database schemas can often be complex and error prone. Changes impact dependent objects and sometimes even the underlying data, and the stakes are high.
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iuui
    
IBM
Published By: Arcserve     Published Date: Feb 26, 2015
In typical organizations, most data resides outside the data center, so it is important that the protection of desktop and laptop computers is given the same priority as file servers and application servers. Have you deployed the right data protection strategy for endpoints? We’re here to help! Arcserve UDP offers a FREE Workstation edition product that specifically focuses on backing up data on endpoints. Not only can desktops and laptops be protected for FREE with award-winning technology that minimizes bandwidth and storage requirements, but they can participate in the global deduplication schema offered by UDP (for 30 days), and have their data protected in public and private clouds, and more! This is too good to pass up! Get your FREE Arcserve UDP Workstation edition now.
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arcserve, unified data protection, software download, bandwidth, deduplication
    
Arcserve
Published By: General Atomics     Published Date: Jan 13, 2015
The term “Big Data” has become virtually synonymous with “schema on read” unstructured data analysis and handling techniques like Hadoop. These “schema on read” techniques have been most famously exploited on relatively ephemeral human-readable data like retail trends, twitter sentiment, social network mining, log files, etc.
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general atomics, big data, metadata, nirvana, hadoop
    
General Atomics
Published By: IBM     Published Date: Jan 10, 2014
The testing of service-oriented architectures and other distributed systems, for more than a decade, has provided a wealth of expertise. Eight key lessons about avoiding some of the most common testing pitfalls are described, together with methods for mitigating certain issues.
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ibm, testing, service-oriented, architecture, service oriented architecture, soa, soa applications, mitigation
    
IBM
Published By: Safe Software     Published Date: Aug 21, 2009
One of the most powerful aspects of GML is the freedom it gives users to define their own custom application schemas. While this capability provides extraordinary flexibility to data modellers, it also creates significant challenges, particularly when the data is interpreted.
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spatial, geographic information system, geographic information systems, geological, geography, information management, data processing, database
    
Safe Software
Published By: SchemaLogic     Published Date: Jun 11, 2008
SchemaLogic Enterprise Suite for Microsoft SharePoint 2007 (SES) resolves SharePoint issues by providing a framework that enables companies to model and connect the structures and relationships of the metadata across the entire SharePoint environment. SES continuously updates and synchronizes metadata across SharePoint site collections, Web applications and farms by leveraging and extending SharePoint’s native capabilities.
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schemalogic, sharepoint, business tools, productivity, collaboration, collaboration tool, share point, microsoft
    
SchemaLogic
Published By: SchemaLogic     Published Date: Jun 11, 2008
In the Life Sciences industry, information is the source of innovation. Vast varieties of content and information sources feed the development pipeline. The ability to create, share, navigate, find and protect essential information is critical to research and development groups, clinicians, regulatory agencies, marketing teams, and those who benefit the most - customers.
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pharm, pharmaceutical, pharmaceuticals, medicine, life science, chemistry, chemical, biological
    
SchemaLogic
Published By: SchemaLogic     Published Date: Jun 11, 2008
Oil & Gas companies operate in an increasingly complex environment. SchemaLogic's enterprise solution for managing content and document metadata enables Oil & Gas companies to model, update and synchronize content across project document repositories or collections for greater reliability and reduced total installed cost.
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mdm, metadata management, oil, gas, petroleum, energy, content management, document management
    
SchemaLogic
Published By: SchemaLogic     Published Date: Jun 11, 2008
Chevron and its subsidiaries use Microsoft SharePoint 2007 to share and exchange information. Yet, it was still a challenge for offices in one part of the world to use materials created by an office in another part of the world. And, the amount of information, shared electronically, was growing exponentially. As a result, the company faced a bit of chaos and a productivity hurdle that begged for more muscle.
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chevron, schemalogic, oil, gas, collaboration, sharepoint, share point
    
SchemaLogic
Published By: SchemaLogic     Published Date: Jun 11, 2008
SchemaLogic of Kirkland, WA, provider of business semantics management software, announced that Chevron has chosen SchemaLogic Enterprise Suite as a critical software component for Phase 3 of the company's third-generation Global Information Link (GIL3) initiative. This strategic initiative defines Chevron's overall information management strategy, global hardware and software architecture and operating environment.
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schemalogic, oil, gas, petroleum, sharepoint, share point, collaboration, chevron
    
SchemaLogic
Published By: SchemaLogic     Published Date: Jun 11, 2008
Kellysearch, a division of Reed Business Information (RBI), is the largest business-to-business (B2B) search portal in Europe. As the web became the primary destination to find information for Kellysearch customers, the need to monetize that content became more urgent in order to stay viable. Kellysearch needed to convert its approach to maximize those opportunities and innovate revenue streams. RBI decided it needed a new infrastructure in order to respond to the demand for timely information and more specific subject matter.
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content, content delivery, cms, content management, schemalogic, content integration, kellysearch, kelly search
    
SchemaLogic
Published By: SchemaLogic     Published Date: Jun 11, 2008
For one of the largest medical research companies in the world, an integrated, global Enterprise Content Management suite of products became essential to locate content growing at an exponential rate. The company conducts massive research projects that marry science with the human experience to develop medications which help people around the world manage their health, live better, and in some cases, cure illness.
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schemalogic, pharmaceutical, pharm, pharma, pharmaceuticals, merck, content management, content delivery
    
SchemaLogic
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