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Published By: DATAVERSITY     Published Date: Nov 05, 2014
Ask any CEO if they want to better leverage their data assets to drive growth, revenues, and productivity, their answer will most likely be “yes, of course.” Ask many of them what that means or how they will do it and their answers will be as disparate as most enterprise’s data strategies. To successfully control, utilize, analyze, and store the vast amounts of data flowing through organization’s today, an enterprise-wide approach is necessary. The Chief Data Officer (CDO) is the newest member of the executive suite in many organizations worldwide. Their task is to develop and implement the strategies needed to harness the value of an enterprise’s data, while working alongside the CEO, CIO, CTO, and other executives. They are the vital “data” bridge between business and IT. This paper is sponsored by: Paxata and CA Technologies
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chief data officer, cdo, data, data management, research paper, dataversity
    
DATAVERSITY
Published By: DATAVERSITY     Published Date: Nov 20, 2015
The competitive advantages realized from a dependable Business Intelligence and Analytics (BI/A) are well documented. Everything from reduced business costs and increased customer retention to better decision making and the ability to forecast opportunities have been observed outcomes in response to such programs. The implementation of such a program remains a necessity for any growing or mature enterprise. The establishment of a comprehensive BI/A program that includes traditional Descriptive Analytics along with next generation categories such as Predictive or Prescriptive Analytics is indispensable for business success.
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DATAVERSITY
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: TopQuadrant     Published Date: Jun 11, 2018
Data governance is a lifecycle-centric asset management activity. To understand and realize the value of data assets, it is necessary to capture information about them (their metadata) in the connected way. Capturing the meaning and context of diverse enterprise data in connection to all assets in the enterprise ecosystem is foundational to effective data governance. Therefore, a data governance environment must represent assets and their role in the enterprise using an open, extensible and “smart” approach. Knowledge graphs are the most viable and powerful way to do this. This short paper outlines how knowledge graphs are flexible, evolvable, semantic and intelligent. It is these characteristics that enable them to: • capture the description of data as an interconnected set of information that meaningfully bridges enterprise metadata silos. • deliver integrated data governance by addressing all three aspects of data governance — Executive Governance, Representative Governance, and App
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TopQuadrant
Published By: Access Sciences     Published Date: Sep 07, 2014
Few organizations have fully integrated the role of the Data Steward due to concerns about additional project complexity, time away from other responsibilities or insufficient value in return. The principles of the Agile methodology (whether or not Agile is followed for projects) can offer guidance in making the commitment to designating and empowering the Data Steward role. By placing insightful people in a position to connect innovators, respond to change and spur development aligned with business activities, organizations can expect to see a more efficient and effective use of their information assets.
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Access Sciences
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: Basho     Published Date: Sep 30, 2016
The Internet of Things (IoT) or the Internet of Everything is changing the way companies interact with their customers and manage their data. These connected devices generate high volume time series data that can be created in milliseconds. This fast growth of IoT data and other time series data is producing challenges for enterprise applications where data must be collected, saved, and analyzed in the blink of an eye. Your application needs a database built to uniquely handle time series data to ensure your data is continuously available and accurate.Learn about the only NoSQL database optimized for IoT and Time Series data in this technical overview. Riak TS stores and analyzes massive amounts of data and is designed to be faster than Cassandra.
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Basho
Published By: AnalytixDS     Published Date: Feb 28, 2015
With future business intelligence solutions clearly evolving from data that comes from highly efficient and well behaved systems, to data that comes from the extended enterprise where data is not necessarily so well structured and behaved - Organizations are forced into a more collaborative mode of operation with their core infrastructure being adapted from the consumer space, and to the extent possible, conformed to their existing repositories. This whitepaper attempts to address various challenges consumers face while managing enormous data sets within the context of this complex scenario. Further, we’ll try to answer the question: Is Big Data Governance really that different from traditional data governance initiatives? Finally, we’ll see how AnalytiX™ Mapping Manager™ can help organizations accelerate the development and deployment of a successful Big Data/ Business Intelligence platform and accelerate delivery of all sorts of data – structured, semi-structured as well as unstruc
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big data, big data governance, data governance, analytixds
    
AnalytixDS
Published By: Neo Technology     Published Date: Feb 15, 2018
By itself, data offers finite value. But when connected, its value is infinite. Discover how enterprise organizations such as Airbnb, eBay and Telia used connected data and graph technology in order to create a sustainable competitive advantage. This white paper shows business leaders how to take advantage of data relationships with graph technology.
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Neo Technology
Published By: Silwood Technology     Published Date: Nov 28, 2016
Business functions in large organizations are usually handled by software application packages. Some of the most well-known of these are from SAP, Oracle, Salesforce and Microsoft. These packages all store their data in a database. Often however it is necessary to use that data with other IT projects. In this instance being able to understand the metadata that defines these databases is critical. The challenge is that their metadata is complex, opaque and difficult to access. This paper describes how the top application packages store and use their own metadata. It explores the importance of understanding that metadata and examines the obstacles in getting at that metadata in a timely and effective manner.
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Silwood Technology
Published By: Silwood Technology     Published Date: Mar 21, 2017
Business functions in large organizations are usually handled by software application packages. Some of the most well-known of these are from SAP, Oracle, Salesforce and Microsoft. These packages all store their data in a database. Often however it is necessary to use that data with other IT projects. In this instance being able to understand the metadata that defines these databases is critical. The challenge is that their metadata is complex, opaque and difficult to access. This paper describes how the top application packages store and use their own metadata. It explores the importance of understanding that metadata and examines the obstacles in getting at that metadata in a timely and effective manner.
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Silwood Technology
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: 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: Erwin     Published Date: Jun 12, 2018
A strong data governance foundation underpins data security and privacy. Find out how to connect the dots across the data trinity – governance, security and privacy – and to act accordingly.
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Erwin
Published By: TopQuadrant     Published Date: Jul 18, 2016
With information streaming in from more varied sources and at a faster pace than ever before, organizations are having an increasingly difficult time deriving accurate meaning from their data. Data governance systems that were once able to organize and process enterprise information are becoming too slow and limited.   Semantic information management makes it easier to reconcile data from different sources by compiling and organizing information about that data, its metadata. By connecting all kinds of data and metadata in a more accessible way, semantic information systems empower users, data stewards and analysts to unlock and use the true meaning and value of their organization’s data.     Learn more about the challenges in the evolving data landscape and how a semantic approach can help.
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TopQuadrant
Published By: TopQuadrant     Published Date: Aug 01, 2016
With information streaming in from more varied sources and at a faster pace than ever before, organizations are having an increasingly difficult time deriving accurate meaning from their data. Data governance systems that were once able to organize and process enterprise information are becoming too slow and limited. Semantic information management makes it easier to reconcile data from different sources by compiling and organizing information about that data, its metadata. By connecting all kinds of data and metadata in a more accessible way, semantic information systems empower users, data stewards and analysts to unlock and use the true meaning and value of their organization’s data. Learn more about the challenges in the evolving data landscape and how a semantic approach can help.
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TopQuadrant
Published By: Red Hat     Published Date: Aug 22, 2018
Digital transformation projects present many technological and organizational challenges. A key challenge is developing modern, cloud-native applications that connect customers directly using automated business processes and decisions. Creating these applications requires a radical change in how software is built—moving away from traditional, IT-led software development to a process that lets both developers and business experts contribute directly to application logic.
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Red Hat
Published By: Akamai Technologies     Published Date: Jun 14, 2018
"Businesses continue to evolve as digital technologies reshape industries. The workforce is mobile, and speed and ef ciency are imperative, necessitating dynamic, cloud-based infrastructures and connectivity, as well as unhindered, secure application access — from anywhere, on any device, at any time. Leaders must remove hurdles to progress, but new business initiatives and processes increase the attack surface, potentially putting the company at risk.
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digital technology, cloud, security, connectivity, authenticate
    
Akamai Technologies
Published By: Akamai Technologies     Published Date: Jun 14, 2018
It’s likely not a matter of if, but when your company will fall prey to targeted attack involving malware, ransomware, data exfiltration, or phishing. In fact, 70% of organizations reported a security incident that negatively impacted their business in the past year. Learn more about the realities of cybercrime in today’s hyperconnected world.
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cybercrime, security, malware
    
Akamai Technologies
Published By: CA Technologies EMEA     Published Date: Sep 30, 2018
If you’re relying on manual processes for testing applications, artificial and automated intelligence (AI) and machine learning (ML) can help you build more efficient continuous frameworks for quality delivery. In this on-demand webinar, “Continuous Intelligent Testing: Applying AI and ML to Your Testing Practices,” you’ll learn how to: Use AI and ML as the new, necessary approach for testing intelligent applications. Strategically apply AI and ML to your testing practices. Identify the tangible benefits of continuous intelligent testing. Reduce risk while driving test efficiency and improvement. This webinar offers practical steps to applying AI and ML to your app testing. The speaker, Jeff Scheaffer, is senior vice president and general manager of the Continuous Delivery Business Unit at CA Technologies. His specialties include DevOps, Mobility, Software as a Service (SaaS) and Continuous Delivery (CDCI).
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continuous delivery, application delivery, testing, test data management
    
CA Technologies EMEA
Published By: CA Technologies EMEA     Published Date: Sep 10, 2018
Companies struggle to find the right test data when testing applications which leads to bottlenecks, defects and constant delays. There is a better way and we want to show you how: Join us for this webcast to learn: - How Test Data Manager finds, builds, protects and delivers test data fast! - How to get your testing teams moving towards self sufficiency with test data Get your questions answered. Come away happy! Recorded Aug 20 2018 60 mins Presented by Prashant Pandey, CA Technologies
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continuous delivery, application delivery, testing, test data management
    
CA Technologies EMEA
Published By: CA Technologies EMEA     Published Date: Sep 11, 2018
Qualsiasi elemento che entra in contatto con l'applicazione migliora o peggiora le performance. Stabilire se ciò sia attribuibile all'infrastruttura, a una variazione del codice, a un'API, alla rete, all'architettura applicativa o a un servizio connesso è estremamente complesso.In questo eBook, descriveremo i nuovi ambienti estremamente articolati e complessi necessari per supportare un business digitale moderno e analizzeremo come un modello inedito di APM (Application Performance Management) possa fornire informazioni fruibili fondamentali per massimizzare le prestazioni.
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CA Technologies EMEA
Published By: CA Technologies EMEA     Published Date: Sep 11, 2018
Casi todo lo que toca una aplicación acaba por mejorar o degradar su rendimiento. El reto es determinar si es atribuible a la infraestructura, un cambio en el código, una API, la red, la arquitectura de la aplicación o un servicio conectado. En este libro electrónico, tratamos los nuevos entornos altamente complejos y caóticos necesarios para dar soporte a un negocio digital moderno y cómo un nuevo modelo de gestión del rendimiento de las aplicaciones (APM) puede proporcionar los conocimientos prácticos necesarios para maximizar el rendimiento.
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CA Technologies EMEA
Published By: CA Technologies EMEA     Published Date: Sep 11, 2018
At a Glance: With the new CA Project & Portfolio Management (CA PPM) 15.3, you can tailor projects to any business unit with drag and-drop ease. Whether complex workflow for HR or simple task management for sales, workers now spin up projects in minutes—not days. Add in-app collaboration to eliminate redundant meetings, a familiar Microsoft Excel®-like grid to manage budgets, a new connection for third-party business intelligence (BI) tools to unearth answers, and you have the most modern project portfolio management app on the market today. Download this whitepaper today to find out more about CA PPM 15.3—a simple, powerful and practical project portfolio management tool available on-premises and in the cloud—let you modernize the project management office.
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CA Technologies EMEA
Published By: CA Technologies EMEA     Published Date: Sep 13, 2018
Introduzione La forza lavoro di oggi è abituata a utilizzare tecnologie personali che semplificano le comunicazioni e la vita quotidiana. Molti strumenti aziendali, tuttavia, non sono riusciti a rimanere al passo. La maggior parte delle attuali soluzioni di project and portfolio management non è in grado di fornire modi semplici per svolgere le attività quotidiane. Non facilitano le comunicazioni contestuali che agevolerebbero la risoluzione dei problemi e non dispongono di funzionalità chiave: capacità di restringere il focus ai dati pertinenti, di eseguire il drill-down per accedere a ulteriori informazioni e di prevedere in modo efficiente le necessità finanziarie e modellare i risultati.
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CA Technologies EMEA
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