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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: 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: 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: DATAVERSITY     Published Date: Oct 11, 2018
The foundation of this report is a survey conducted by DATAVERSITY® that included a range of different question types and topics on the current state of Data Governance and Data Stewardship. The report evaluates the topic through a discussion and analysis of each presented survey question, as well as a deeper examination of the present and future trends.
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DATAVERSITY
Published By: MapR Technologies     Published Date: Aug 04, 2018
Legacy infrastructures simply cannot handle the workloads or power the applications that will drive business decisively forward in the years ahead. New infrastructure, new thinking and new approaches are in the offing, all driven by the mantra 'transform or die.' This book is meant for IT architects; developers and development managers; platform architects; cloud specialists; and big data specialists. For you, the goal is to help create a sense of urgency you can present to your CXOs and others whose buy-in is needed to make essential infrastructure investments along the journey to digital transformation.
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MapR Technologies
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: Syncsort     Published Date: Oct 30, 2018
In today’s digital business world, accurate address and geolocation data is invaluable. But, address capture is something that is often overlooked from a user and business perspective. Clean address capture can enhance user experience, not only while entering an address, but also during the entire customer journey. Download this eBook to learn how global address validation tools can help: • Simplify address capture on web-based forms • Accurately pinpoint customer locations • Improve efficiencies in shipping and logistics • Define sales and marketing territories and enrich address information
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Syncsort
Published By: Syncsort     Published Date: Oct 31, 2018
Assessing data quality on an ongoing basis is necessary to know how well the organization is doing at maximizing data quality. Otherwise, you’ll be investing time and money in a data quality strategy that may or may not be paying off. To measure data quality and track the effectiveness of data quality improvement efforts, you need – well...data. What does a data quality assessment look like in practice? Read this eBook for a further look into four ways to measure data quality.
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Syncsort
Published By: Octopai     Published Date: Sep 01, 2018
For many BI professionals, every task can feel like MISSION IMPOSSIBLE. All the manual mapping required to sort out inconsistencies in data and the lack of tools to simplify and shorten the process of finding and understanding data leaves BI groups frustrated and slows down the business. This whitepaper examines the revolutionary impact of automation on the cumbersome manual processes that have been dragging BI down for so long. • Data correction vs process correction • Root-cause analysis with data lineage: reverse-tracing the data flow • Data quality rules and data controls • Automated data lineage mapping
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Octopai
Published By: Red Gate     Published Date: May 09, 2018
This whitepaper looks at what the changing data privacy and protection landscape means for organizations.
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Red Gate
Published By: Wave Computing     Published Date: Jul 06, 2018
This paper argues a case for the use of coarse grained reconfigurable array (CGRA) architectures for the efficient acceleration of the data flow computations used in deep neural network training and inferencing. The paper discusses the problems with other parallel acceleration systems such as massively parallel processor arrays (MPPAs) and heterogeneous systems based on CUDA and OpenCL, and proposes that CGRAs with autonomous computing features deliver improved performance and computational efficiency. The machine learning compute appliance that Wave Computing is developing executes data flow graphs using multiple clock-less, CGRA-based System on Chips (SoCs) each containing 16,000 processing elements (PEs). This paper describes the tools needed for efficient compilation of data flow graphs to the CGRA architecture, and outlines Wave Computing’s WaveFlow software (SW) framework for the online mapping of models from popular workflows like Tensorflow, MXNet and Caffe.
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Wave Computing
Published By: TD Bank Group     Published Date: Aug 10, 2018
This paper examines whether blockchain distributed ledger technology could improve the management of trusted information, specifically considering data quality. Improvement was determined by considering the impact of a distributed ledger as an authoritative source in TD Bank Group's Enterprise Data Quality Management Process versus the use of standard authoritative sources such as databases and files. Distributed ledger technology is not expected, or proven, to result in a change in the Data Quality Management process. Our analysis focused on execution advantages possible due to distributed ledger properties that make it an attractive resource for data quality management (DQM).
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TD Bank Group
Published By: Attunity     Published Date: Sep 21, 2018
Apache NiFi is an easy to use, powerful, and reliable system to process and distribute data. It provides an end-to-end platform that can collect, curate, analyze, and act on data in real-time, on-premises, or in the cloud with a drag-and-drop visual interface. This book offers you an overview of NiFi along with common use cases to help you get started, debug, and manage your own dataflows.
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Attunity
Published By: Attunity     Published Date: Oct 19, 2018
Change data capture (CDC) technology can modernize your data and analytics environment with scalable, efficient and real-time data replication that does not impact production systems. To realize these benefits, enterprises need to understand how this critical technology works, why it’s needed, and what their Fortune 500 peers have learned from their CDC implementations. This book serves as a practical guide for enterprise architects, data managers and CIOs as they enable modern data lake, streaming and cloud architectures with CDC. Read this book to understand: ? The rise of data lake, streaming and cloud platforms ? How CDC works and enables these architectures ? Case studies of leading-edge enterprises ? Planning and implementation approaches
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Attunity
Published By: graphgrid     Published Date: Oct 02, 2018
Whether it’s for a specific application, optimizing your existing operations, or innovating new customer services, graph databases are a powerful technology that turn accessing and analyzing your data into a competitive advantage. Graph databases resolve the Big Data limitations and free up data architects and developers to build amazing solutions that predict behaviors, enable data driven decisions and make insightful recommendations. Yet just as cars aren’t functional with only engines, graph databases require surrounding capabilities including ingesting multi-source data, building data models that are unique to your business needs, ease of data interaction and visualization, seamless co-existence with legacy systems, high performance search capabilities, and integration of data analysis applications. Collectively, this comprehensive data platform turns graph capabilities into tangible insights that drive your business forward.
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graphgrid
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: DATAVERSITY     Published Date: Nov 11, 2013
This report investigates the level of Information Architecture (IA) implementation and usage at the enterprise level. The primary support for the report is an analysis of a 2013 DATAVERSITY™ survey on Data and Information Architecture. This paper is sponsored by: HP, Vertica, Denodo, Embarcadero and CA Technologies.
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information architecture, data architecture, white paper, mdm, master data management, data, data management, enterprise information management, enterprise data management, data virtualization, metadata, data modeling, research paper, survey, data integration
    
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
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