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Published By: DATAVERSITY     Published Date: Dec 27, 2013
There are actually many elements of such a vision that are working together. ACID and NoSQL are not the antagonists they were once thought to be; NoSQL works well under a BASE model, but also some of the innovative NoSQL systems fully conform to ACID requirements. Database engineers have puzzled out how to get non-relational systems to work within an environment that demands high availability, scalability, with differing levels of recovery and partition tolerance. BASE is still a leading innovation that is wedded to the NoSQL model, and the evolution of both together is harmonious. But that doesn’t mean they always have to be in partnership; there are several options. So while the opening anecdote is true in many cases, organizations that need more diverse possibilities can move into the commercial arena and get the specific option that works best for them. This paper is sponsored by: MarkLogic.
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nosql, database, acid v base, white paper
    
DATAVERSITY
Published By: First San Francisco Partners     Published Date: Mar 13, 2015
A Data Governance Organization and its structure should be defined to align with your company’s organizational hierarchy and resources. Finding the right people to assign to data governance requires an understanding of both the functional and the political role of governance within your organization. This paper highlights some best practices in putting the right resources behind the required roles.
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data governance, data governance resources, data governance organization
    
First San Francisco Partners
Published By: First San Francisco Partners     Published Date: Jun 01, 2016
A Data Governance Organization and its structure should be defined to align with your company’s organizational hierarchy and resources. Finding the right people to assign to data governance requires an understanding of both the functional and the political role of governance within your organization. This paper highlights some best practices in putting the right resources behind the required roles.
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First San Francisco Partners
Published By: MarkLogic     Published Date: Aug 04, 2014
The Age of Information and the associated growth of the World Wide Web has brought with it a new problem: how to actually make sense of all the information available. The overarching goal of the Semantic Web is to change that. Semantic Web technologies accomplish this goal by providing a universal framework to describe and link data so that it can be better understood and searched holistically, allowing both people and computers to see and discover relationships in the data. Today, organizations are leveraging the power of the Semantic Web to aggregate and link disparate data, improve search navigation, provide holistic search and discovery, dynamically publish content, and complete ETL processes faster. Read this white paper to gain insight into why Semantics is important, understand how Semantics works, and see examples of Semantics in practice.
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data, data management, whitepaper, marklogic, semantic, semantic technology, nosql, database, semantic web, big data
    
MarkLogic
Published By: CA Technologies     Published Date: Feb 25, 2016
As combinations of both internal and externally-imposed business policies imply dependencies on managed data artifacts, organizations are increasingly instituting data governance programs to implement processes for ensuring compliance with business expectations. One fundamental aspect of data governance involves practical application of business rules to data assets based on data elements and their assigned values. Yet despite the intent of harmonizing data element definitions and resolution of data semantics and valid reference values, most organizations rarely have complete visibility into the metadata associated with enterprise data assets.
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CA Technologies
Published By: Semantic Arts     Published Date: Aug 01, 2013
This White Paper explains how Semantic Technology can help organizations leverage their legacy investments into new solutions through the use of a Semantic Layer so they can improve IT productivity by reducing complexity, thereby reducing total cost of ownership.
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white paper, semantic technology, data, data management
    
Semantic Arts
Published By: Cloudant - an IBM Company     Published Date: Jun 01, 2015
Whether you're a DBA, data scientist or developer, you're probably considering how the cloud can help modernize your information management and analytics strategy. Cloud data warehousing can help you get more value from your data by combining the benefits of the cloud - speed, scale, and agility - with the simplicity and performance of traditional on-premises appliances. This white paper explores how a cloud data warehouse like IBM dashDB can reduce costs and deliver new business insights. Readers will learn about: - How data warehousing-as-a-service helps you scale without incurring extra costs - The benefits of in-database analytics in a cloud data warehouse - How a cloud data warehouse can integrate with the larger ecosystem of business intelligence tools, both on prem and off prem
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nosql, ibm, dashdb, database, cloud
    
Cloudant - an IBM Company
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: Neo Technology     Published Date: Jun 28, 2015
The future of Master Data Management is deriving value from data relationships which reveal more data stories that become more and more important to competitive advantage as we enter into the future of data and business analytics. MDM will be about supplying consistent, meaningful views of master data and being able to unify data into one location, especially to optimize for query performance and data fit. Graph databases offer exactly that type of data/performance fit. Use data relationships to unlock real business value in MDM: - Graphs can easily model both hierarchical and non-hierarchical master data - The logical model IS the physical model making it easier for business users to visualize data relationships - Deliver insights in real-time from data relationships in your master data - Stay ahead of the business with faster development Download and read the white paper Your Master Data Is a Graph: Are You Ready? to learn why your master data is a graph and how graph databases like Neo4j are the best technologies for MDM.
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database, nosql, graph database, big data, master data management, mdm
    
Neo Technology
Published By: VoltDB     Published Date: Feb 12, 2016
The need for fast data applications is growing rapidly, driven by the IoT, the surge in machine-to-machine (M2M) data, global mobile device proliferation, and the monetization of SaaS platforms. So how do you combine real-time, streaming analytics with real-time decisions in an architecture that’s reliable, scalable, and simple? In this report, Ryan Betts and John Hugg from VoltDB examine ways to develop apps for fast data, using pre-defined patterns. These patterns are general enough to suit both the do-it-yourself, hybrid batch/streaming approach, as well as the simpler, proven in-memory approach available with certain fast database offerings.
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VoltDB
Published By: Looker     Published Date: Mar 15, 2016
Data centralization merges different data streams into a common source through unified variables. This process can provide context to overly-broad metrics and enable cross-platform analytics to guide better business decisions. Investments in analytics tools are now paying back a 13.01:1 return on investment (ROI), with increased returns when these tools integrate with three or more data sour- ces. While the perks of centralization are obvious in theory, the quantity and variety of data available in today’s landscape make this difficult to achieve. This report provides a roadmap for how to connect systems, data stores, and institutions (both technological and human). Learn: • How data centralization enables better analytics • How to redefine data as a vehicle for change • How the right BI tool eliminates the data analyst bottleneck • How to define single sources of truth for your organization • How to build a data-driven (not just data-rich) organization
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Looker
Published By: Alation     Published Date: Mar 26, 2018
When analysts and data scientists have access to data governance policies and best practices directly within the flow of their analysis, the result is both more consistent compliance and more broadly adopted best practices. With the combination of Tableau and Alation, organizations can not only balance the demands of agility and governance, they can actually optimize for both at the same time. We call this Governance for Insight. Learn more about how Tableau users can have the best of worlds - agility and governance. Read Enabling Governance for Insight: Trust in Data with Tableau and Alation’s Data Catalogs. Register on the right to access a complimentary copy of this joint white paper from Tableau and Alation.
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Alation
Published By: WhereScape     Published Date: Oct 02, 2018
Like any new initiative, there are both challenges and benefits. It Is advisable to understand both of these when deciding whether cloud computing is suitable for your company’s analytic environment.
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WhereScape
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: Collibra     Published Date: Jul 09, 2018
Data governance can be a game changer when it comes to modern business. But leveraging data for strategic objectives is easier said than done. This new report, developed by the Economist Intelligence Unit, explores the challenges and opportunities for data governance both globally and across industries. Based on a survey of over 500 business executives and complemented by in-depth interviews, this report reveals: • What's working in data governance — and what's not • Why organizations must shift their thinking to data governance on offense • How to overcome barriers to better data governance
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Collibra
Published By: Datawatch     Published Date: Apr 06, 2018
Enterprises are focusing on becoming ever more data-driven, meaning that it is simply unacceptable to allow data to go to waste. Yet, as the amount of data businesses collect and control continues to increase exponentially, many organizations are failing to derive enough business value from their data. Companies are feeling the pressure to extract maximum value from all of their data, both defensive and offensive. Defensive analytics are the “plumbing aspects” of data management that must be captured to mitigate risk and establish a basic understanding of business performance. Offensive analytics build on defensive analytics and support overarching business objectives, strategic initiatives and long-term goals using predictive models. In this whitepaper, you will learn how to address many challenges, including streamlining operational reporting, delivering insight and providing a single, unified platform for everyone.
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Datawatch
Published By: Deloitte Process Robotics     Published Date: May 04, 2018
Deloitte Process Robotics (DPR) solutions use a lightweight approach to train ‘bots’ that automate repetitive tasks of medium complexity without changes to existing process or IT infrastructure. With ever-growing repositories of unanalyzed and underutilized data, organizations require highly flexible and scalable enterprise data management (EDM) processes, DPR makes it possible for organizations to adopt comprehensive yet affordable EDM processes in the Big Data Era, helping organizations transform data into strategic assets through the automation of capabilities.
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Deloitte Process Robotics
Published By: Io-Tahoe     Published Date: May 14, 2018
The “silver lining” in GDPR compliance efforts is a creation of transparency and trust with customers, many of whom have layers of concern and trepidation over how all companies they do business with are handling their data. GDPR compliance efforts offer a chance to clear this air, between organizations and their customers, in a way that’s beneficial to both sides. In Io-Tahoe’s eBook, we explore the obligatory components of GDPR compliance, and the mindset most appropriate to achieving it. We also investigate opportunistic facets of establishing comprehensive protection policy around personal or sensitive data. We look at the prospect of GDPR compliance through the exploration of several “mandates”. Download the e-book to find out more on the eight mandates and the dividends beyond.
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Io-Tahoe
Published By: Collibra     Published Date: Jul 02, 2018
Data governance can be a game changer when it comes to modern business. But leveraging data for strategic objectives is easier said than done. This new report, developed by the Economist Intelligence Unit, explores the challenges and opportunities for data governance both globally and across industries. Based on a survey of over 500 business executives and complemented by in-depth interviews, this report reveals: • What's working in data governance — and what's not • Why organizations must shift their thinking to data governance on offense • How to overcome barriers to better data governance
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Collibra
Published By: DATAVERSITY     Published Date: Jan 21, 2013
This report examines the biggest challenges faced by data modelers at both quantitative and qualitative levels. It discusses the results of four different data modeling surveys in 2007, 2009, 2011, and 2012.
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data management
    
DATAVERSITY
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: TIBCO Software EMEA     Published Date: Jan 17, 2019
Are you considering data virtualization for your organization today? In this paper you will learn 10 core truths about data virtualization and gain essential knowledge for overcoming analytic data bottlenecks and driving better outcomes.
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virtualization, data, analytics, datasets, software, access, integration, projects, tools, scalability
    
TIBCO Software EMEA
Published By: TIBCO Software GmbH     Published Date: Jan 15, 2019
Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202
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TIBCO Software GmbH
Published By: Larsen & Toubro Infotech     Published Date: Jan 24, 2019
All native and ‘transitioning’ media companies are focusing heavily on content to save existing businesses, or building new business models, or both. Television broadcasters, wary of the growing cord-cutting, are spending large sums on premium content. In 2017, the top four media companies spent more than USD 34 billion on original and acquired non-sports programming. Pure-play OTT providers have, on the other hand, bet big on content to shore up on subscribers. Netflix alone spent more than USD 6 billion on content last year, while spend was USD 7 billion for Amazon and Hulu combined. Transitioning media companies, such as telecom and technology companies that are moving towards being a media company, are also allocating sizable funds for content in their quest to explore supplementary businesses, by boosting customer engagement on their platforms. Apple and Facebook have started creating their own original content, and spend is only going to expand further.
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Larsen & Toubro Infotech
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
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