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Published By: Ted Hills     Published Date: Mar 08, 2017
This document provides a complete reference for the Concept and Object Modeling Notation (COMN, pronounced “common”), release 1.1. The book NoSQL and SQL Data Modeling (Technics Publications, 2016) reflects release 1.0 of COMN. This is a reference, not a tutorial. This document is designed to support a quick check of how to draw or notate something in COMN.
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Ted Hills
Published By: DATAVERSITY     Published Date: Jun 14, 2013
This report analyzes many challenges faced when beginning a new Data Governance program, and outlines many crucial elements in successfully executing such a program. “Data Governance” is a term fraught with nuance, misunderstanding, myriad opinions, and fear. It is often enough to keep Data Stewards and senior executives awake late into the night. The modern enterprise needs reliable and sustainable control over its technological systems, business processes, and data assets. Such control is tantamount to competitive success in an ever-changing marketplace driven by the exponential growth of data, mobile computing, social networking, the need for real-time analytics and reporting mechanisms, and increasing regulatory compliance requirements. Data Governance can enhance and buttress (or resuscitate, if needed) the strategic and tactical business drivers every enterprise needs for market success. This paper is sponsored by: ASG, DGPO and DebTech International.
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data, data management, data governance, data steward, dataversity, research paper
    
DATAVERSITY
Published By: Alation     Published Date: Jan 06, 2017
90% of the time that is spent creating new reports is recreating information that already exists. Without a way to effectively share prior work and identify verified data sources, analysts and other data consumers lack shared context on how to apply data to analytic inquiries and business decision making. Time is wasted tracking down subject matter experts and trying to unearth tribal knowledge. Leading analytic organizations in retail, healthcare, financial services and technology are using data catalogs to help their analysts find, understand and use data appropriately. What are the 5 critical capabilities of a data catalog? Learn more here:
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Alation
Published By: Alation     Published Date: Jan 06, 2017
90% of the time that is spent creating new reports is recreating information that already exists. Without a way to effectively share prior work and identify verified data sources, analysts and other data consumers lack shared context on how to apply data to analytic inquiries and business decision making. Time is wasted tracking down subject matter experts and trying to unearth tribal knowledge. Leading analytic organizations in retail, healthcare, financial services and technology are using data catalogs to help their analysts find, understand and use data appropriately. What are the 5 critical capabilities of a data catalog? Learn more here:
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Alation
Published By: Information Asset, LLC     Published Date: Feb 11, 2014
An In-Depth Review of Data Governance Software Tools: Reference Architecture, Evaluation Criteria, and Vendor Landscape
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white paper, data governance, data, data management, data management white paper, data governance white paper
    
Information Asset, LLC
Published By: Paxata     Published Date: Apr 02, 2014
Why Sift Through Data Landfills? Better business insight comes from data - but data is often dirty, incomplete and complicated. As any analyst would admit, what passes for data science is more like janitorial work. Find out why that is - and how you can avoid the painful, manual and error-prone processes that have bogged down the analytics process for 30 years.
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data, data management, big data, white paper, paxata, analytics
    
Paxata
Published By: Basho     Published Date: Mar 08, 2015
Many companies still use relational databases as part of the technology stack. However, others are innovating and incorporating NoSQL solutions and as a result they have simplified their deployments, enhanced their availability and reduced their costs. In this whitepaper you will learn: - Why companies choose Riak over a relational database. - How to analyze the decision points you should consider when choosing between relational and Nosql databases - Simple patters for building common applications in Riak using its key/value design Learn how you can lead your organization into this new frontier.
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data, data management, basho, database, nosql, data models
    
Basho
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: Ted Hills     Published Date: Jul 02, 2015
Entity-relationship (E-R) modeling is a tried and true notation for use in designing Structured Query Language (SQL) databases, but the new data structures that Not-Only SQL (NOSQL) DBMSs make possible can’t be represented in E-R notation. Furthermore, E-R notation has some limitations even for SQL database design. This article shows how a new notation, the Conceptual and Objective Modeling (COM) notation, is able to represent NOSQL designs that are beyond the reach of E-R notation. At the end, it gives a peek into the tutorial workshop to be given at the 2015 NOSQL Conference in San Jose, CA, US, in August, which will provide opportunities to apply COM notation to practical problems.
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nosql, sql, data modeling, data model, er modeling, entity relationship, database, relational, dbms, schema-less, xml, conceptual, logical, physical
    
Ted Hills
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: Experian     Published Date: Mar 30, 2017
Businesses today recognize the importance of the data they hold, but a general lack of trust in the quality of their data prevents them from achieving strategic business objectives. Nearly half of organizations globally say that a lack of trust in their data contributes to increased risk of non-compliance and regulatory penalties (52%) and a downturn in customer loyalty (51%). To be of value to organizations, data needs to be trustworthy. In this report, you will read about the findings from this unique study, including: · How data powers business opportunities · Why trusted data is essential for performance · Challenges that affect data quality · The current state of data management practices · Upcoming data-related projects in 2017
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Experian
Published By: Experian     Published Date: Mar 12, 2018
Data is quickly becoming the currency of the emerging digital economy. As digital transformation efforts proliferate and become commonplace, data will take center stage as a critical driver of these initiatives. Organizations that are able to mobilize their data assets to power critical business initiatives will see a distinct advantage in the years to come. In fact, a majority of C-level executives (87%) believe that data has greatly disrupted their organization’s operations over the last 12 months. As the reliance on data deepens, the need for trustworthy and reliable data assets will become increasingly important. This year’s global study highlights several important issues and opportunities throughout the data management and data quality spaces. By discussing the latest advancements and challenges within our industry, we hope to empower all organizations to better leverage their data and to thrive in the digital economy.
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Experian
Published By: Experian     Published Date: Mar 12, 2018
Data is quickly becoming the currency of the emerging digital economy. As digital transformation efforts proliferate and become commonplace, data will take center stage as a critical driver of these initiatives. Organizations that are able to mobilize their data assets to power critical business initiatives will see a distinct advantage in the years to come. In fact, a majority of C-level executives (87%) believe that data has greatly disrupted their organization’s operations over the last 12 months. As the reliance on data deepens, the need for trustworthy and reliable data assets will become increasingly important. This year’s global study highlights several important issues and opportunities throughout the data management and data quality spaces. By discussing the latest advancements and challenges within our industry, we hope to empower all organizations to better leverage their data and to thrive in the digital economy.
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Experian
Published By: Experian     Published Date: Jun 01, 2018
Better data insight is the key to becoming a more informed, profitable company. Download this white paper to understand: -How to overcome challenges you may have with your data management strategy -What improvements you should make that will make the biggest impact -The importance of being proactive rather than reactive to data quality issues
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Experian
Published By: Reltio     Published Date: Nov 16, 2018
Explore this 31-criteria, Forrester Wave Report on MDM platforms and vendors. You'll discover an evaluation of 12 vendors including leader Reltio with modern Master Data Management.
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Reltio
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: FairCom     Published Date: May 25, 2016
As companies embrace NoSQL as the “next big thing,” they are rightly cautious of abandoning their investment in SQL. The question a responsible developer or IT manager must investigate is “in which cases are each of these technologies, SQL and NoSQL, the appropriate solution?” For example, cloud provider BigStep offered this assessment: “NoSQL is not the best model for OLTP, ad hoc queries, complicated relationships among the data, and situations when stability and reliability outweigh the importance of speed.” While that statement may be true of many NoSQL databases, c-treeACE is the exception. Its unique, No+SQL architecture offers the advantages of SQL on top of a robust, high-performance NoSQL core engine. In this white paper, you'll read five ways c-treeACE breaks the NoSQL mold in terms of: • Data Integrity • Availability and Reliability • Complex Data Relationships • Flexible Queries • Performance
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FairCom
Published By: MariaDB     Published Date: Apr 02, 2018
Learn how to use JSON functions for semi-structured data This white paper explains step-by-step how to support semi-structured data with JSON functions, introduced in MariaDB Server 10.2, using a practical use case with sample data and queries for everything from creating, reading and querying JSON documents to enforcing data integrity with check constraints and functions. You will learn how to: • Create, read and update JSON documents • Index and query JSON documents • Enforce data integrity with JSON documents • Combine relational data and JSON documents • Return JSON documents as relational data • Return relational data as JSON documents
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MariaDB
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: Experian     Published Date: Nov 03, 2015
It is critically important for businesses today to leverage data as a strategic asset, instead of allowing it to become an obstacle. As more and more organizations are trying to make smarter, data-driven decisions, they are discovering that their data management strategy may not be as mature as it needs to be. One major shift we are seeing is the implementation of a Chief Data Officer. Experian Data Quality recently conducted a research study of more than 250 Chief Information Officers (CIOs) and Chief Data Officers (CDOs) in the US about their data management practices, and the explosion of the CDO role. Key insights in the report include: - Tips for overcoming typical data challenges within your organization - The changing data management landscape and its affect on the CIO - The new and growing need for the CDO - And more!
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Experian
Published By: DATAVERSITY     Published Date: Dec 23, 2013
Everyone in an organization relies on Metadata to do their jobs. Whenever an email is sent, a report is run, inventory is ordered, compliance procedures are verified, a new IT system is integrated, applications are executed, or essentially any other business function, process, or decision is undertaken, Metadata is facilitating in the background. If that Metadata is corrupt, missing, redundant, or unpredictable then they cannot do their jobs well, they cannot trust the data they are using, and the organization ultimately suffers at all levels. Data Stewards are the people who are use, define, cleanse, archive, analyze, and share the data that is mapped directly to the Metadata of their myriad database and application systems. If your organization does not have Data Stewards (or an inefficient Stewardship Program), you need them. This paper is sponsored by: ASG.
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DATAVERSITY
Published By: ASG     Published Date: Jun 10, 2013
Everyone in an organization relies on Metadata to do their jobs. Whenever an email is sent, a report is run, inventory is ordered, compliance procedures are verified, a new IT system is integrated, applications are executed, or essentially any other business function, process, or decision is undertaken, Metadata is facilitating in the background. If that Metadata is corrupt, missing, redundant, or unpredictable then they cannot do their jobs well, they cannot trust the data they are using, and the organization ultimately suffers at all levels. Data Stewards are the people who are use, define, cleanse, archive, analyze, and share the data that is mapped directly to the Metadata of their myriad database and application systems. If your organization does not have Data Stewards (or an inefficient Stewardship Program), you need them.
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asg, data, data management, data governance, white paper, dataversity, data steward, metadata
    
ASG
Published By: DATAVERSITY     Published Date: Jun 17, 2013
This report analyzes many challenges faced when beginning a new Data Governance program, and outlines many crucial elements in successfully executing such a program. “Data Governance” is a term fraught with nuance, misunderstanding, myriad opinions, and fear. It is often enough to keep Data Stewards and senior executives awake late into the night. The modern enterprise needs reliable and sustainable control over its technological systems, business processes, and data assets. Such control is tantamount to competitive success in an ever-changing marketplace driven by the exponential growth of data, mobile computing, social networking, the need for real-time analytics and reporting mechanisms, and increasing regulatory compliance requirements. Data Governance can enhance and buttress (or resuscitate,if needed) the strategic and tactical business drivers every enterprise needs for market success.
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research paper, data, data management, data governance, data steward
    
DATAVERSITY
Published By: TIBCO Software     Published Date: Mar 15, 2019
On-demand Webinar The current trend in manufacturing is towards tailor-made products in smaller lots with shorter delivery times. This change may lead to frequent production modifications resulting in increased machine downtime, higher production cost, product waste—and the need to rework faulty products. Watch this webinar to learn how TIBCO’s Smart Manufacturing solutions can help you overcome these challenges. You will also see a demonstration of TIBCO technology in action around improving yield and optimizing processes while also saving costs. What You Will Learn: Applying advanced analytics & machine learning / AI techniques to optimize complex manufacturing processes How multi-variate statistical process control can help to detect deviations from a baseline How to monitor in real time the OEE and produce a 360 view of your factory The webinar also highlights customer case studies from our clients who have already successfully implemented process optimization models. Speakers:
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TIBCO Software
Published By: Zendesk     Published Date: Jan 04, 2019
Seus clientes eles entendem mais de tecnologia do que nunca e preferem a abordagem "faça você mesmo" para resolver seus problemas e responder às suas próprias dúvidas. Anos de pesquisas feitas pelo ICMI confirmaram que os clientes preferem resolver seus problemas por conta própria e usando seus canais favoritos. Além disso, os clientes só procuram interações diretas quando esgotam todas as opções de autoatendimento. Essa informação se baseia em dados da American Express, que descobriu que 48% dos consumidores preferem falar com um representante do atendimento ao cliente para lidar com problemas complexos, mas apenas 16% preferem esse mesmo contato para resolver problemas simples. O objetivo desse documento é simples: queremos ajudá-lo a criar uma base de conhecimento, uma comunidade e um portal do cliente completos. E você pode fazer tudo isso usando a Central de Ajuda do Zendesk Guide.
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Zendesk
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