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Published By: Syncsort     Published Date: Feb 21, 2019
With data lakes offering the means to capture, store and utilize a broad array of internal, third party and external data from a variety of sources, organizations of all types are ready to gain greater and better insights. While this promise of Big Data and improved visibility is substantial, data is pretty much useless if it can’t be trusted. The only way to be certain that your data governance policies are consistently followed and enforced is to ensure data quality across your IT systems. Download this white paper with Information Management, Discover the Value of Data Quality for Data Governance Success, to learn more about empowering your data governance program with quality data.
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Syncsort
Published By: DATAVERSITY     Published Date: Jul 24, 2014
Will the “programmable era” of computers be replaced by Cognitive Computing systems which can learn from interactions and reason through dynamic experience just like humans? With rapidly increasing volumes of Big Data, there is a compelling need for smarter machines to organize data faster, make better sense of it, discover insights, then learn, adapt, and improve over time without direct programming. This paper is sponsored by: Cognitive Scale.
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data, data management, cognitive computing, machine learning, artificial intelligence, research paper
    
DATAVERSITY
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: 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: 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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data, data management, analytics, business intelligence, data science
    
DATAVERSITY
Published By: DATAVERSITY     Published Date: Oct 04, 2016
This report evaluates each question posed in a recent survey and provides subsequent analysis in a detailed format that includes the most noteworthy statistics, direct comments from survey respondents, and the influence on the industry as a whole. It seeks to present readers with a thorough review of the state of Metadata Management as it exists today.
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DATAVERSITY
Published By: Ted Hills     Published Date: Mar 08, 2017
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.
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Ted Hills
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: Ted Hills     Published Date: Mar 08, 2017
This paper explores the differences between three situations that appear on the surface to be very similar: a data attribute that may occur zero or one times, a data attribute that is optional, and a data attribute whose value may be unknown. It shows how each of these different situations is represented in Concept and Object Modeling Notation (COMN, pronounced “common”). The theory behind the analysis is explained in greater detail by three papers: Three-Valued Logic, A Systematic Solution to Handling Unknown Data in Databases, and An Approach to Representing Non-Applicable Data in Relational Databases.
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Ted Hills
Published By: Ted Hills     Published Date: Mar 08, 2017
Much has been written and debated about the use of SQL NULLs to represent unknown values, and the possible use of three-valued logic. However, there has never been a systematic application of any three-valued logic to use in the logical expressions of computer programs. This paper lays the foundation for a systematic application of three-valued logic to one of the two problems inadequately addressed by SQL NULLs.
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Ted Hills
Published By: Ted Hills     Published Date: Mar 08, 2017
Ever since Codd introduced so-called “null values” to the relational model, there have been debates about exactly what they mean and their proper handling in relational databases. In this paper I examine the meaning of tuples and relations containing “null values”. For the type of “null value” representing unknown data, I propose an interpretation and a solution that is more rigorously defined than the SQL NULL or other similar solutions, and which can be implemented in a systematic and application-independent manner in database management systems.
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Ted Hills
Published By: Ted Hills     Published Date: Mar 08, 2017
Ever since Codd introduced so-called “null values” to the relational model, there have been debates about exactly what they mean and their proper handling in relational databases. In this paper I examine the meaning of tuples and relations containing “null values”. For the type of “null value” representing that data are not applicable, I propose an interpretation and a solution that is more rigorously defined than the SQL NULL or other similar solutions, and which can be implemented in a systematic and application-independent manner in database management systems.
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Ted Hills
Published By: CData     Published Date: Jan 04, 2019
The growth of NoSQL continues to accelerate as the industry is increasingly forced to develop new and more specialized data structures to deal with the explosion of application and device data. At the same time, new data products for BI, Analytics, Reporting, Data Warehousing, AI, and Machine Learning continue along a similar growth trajectory. Enabling interoperability between applications and data sources, each with a unique interface and value proposition, is a tremendous challenge. This paper discusses a variety of mapping and flattening techniques, and continues with examples that highlight performance and usability differences between approaches.
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data architecture, data, data management, business intelligence, data warehousing
    
CData
Published By: DATAVERSITY     Published Date: Feb 27, 2013
In its most basic definition, unstructured data simply means any form of data that does not easily fit into a relational model or a set of database tables.
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white paper, dataversity, unstructured data, enterprise data management, data, data management
    
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: CA Technologies     Published Date: Oct 22, 2015
As the interest in managing information and enforcing corporate data management policies increases, data governance programs to manage data sets are becoming more and more vital to the business operation. However, in this rush for data governance programs, sometimes the true utility and importance of metadata can be missed. In this white paper, David Loshin of Knowledge Integrity, Inc. discusses the importance of data governance and the role of metadata management as a way to empower data governance and enforce data policies.
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white paper, metadata, data management, data modeling, david loshin, data governance, data governance strategy
    
CA Technologies
Published By: Trillium Software     Published Date: Dec 17, 2015
Digital business and disruptive technologies continue to fuel solid growth in the data quality tools market, alongside traditional cost reduction and process optimization efforts. This Magic Quadrant will help CIOs, chief data officers and information leaders find the best vendor for their needs.
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Trillium Software
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: Stardog Union     Published Date: Jul 27, 2018
When enterprises consider the benefits of data analysis, what's often overlooked is the challenge of data variety, and that most successful outcomes are driven by it. Yet businesses are still struggling with how to query distributed, heterogeneous data using a unified data model. Fortunately, Knowledge Graphs provide a schema flexible solution based on modular, extensible data models that evolve over time to create a truly unified solution. How is this possible? Download and discover: • Why businesses should organize information using nodes and edges instead of rows, columns and tables • Why schema free and schema rigid solutions eventually prove to be impractical • The three categories of data diversity including semantic and structural variety
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Stardog Union
Published By: Dell Boomi     Published Date: May 29, 2013
Application and data integration doesn't have to be slow and expensive. New cloud-based integration platforms dramatically speed results and lower costs, as outlined in this new report by Bloor Research.
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Dell Boomi
Published By: Dell Boomi     Published Date: May 28, 2013
Application and data integration doesn't have to be slow and expensive. New cloud-based integration platforms dramatically speed results and lower costs, as outlined in this new report by Bloor Research.
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Dell Boomi
Published By: DATAVERSITY     Published Date: May 25, 2014
Deconstructing NoSQL: Analysis of a 2013 Survey on the Use, Production, and Assessment of NoSQL Technologies in the Enterprise This report examines the non-relational database environment from the viewpoints of those within the industry–whether current or future adopters, consultants, developers, business analysts, vendors, or others. This paper is sponsored by: MarkLogic, Cloudant and Neo4j.
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research paper, analysis, nosql, database, nosql database, white paper, nosql 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: 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
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