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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: 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: graphgrid     Published Date: Oct 19, 2018
Graph databases are about to catapult across the famous technology adoption chasm and land in start-ups, enterprises and government agencies across the globe. The adoption antibodies are subsiding as the power of natively connected data becomes fundamental to any organization looking for data-driven insights across operations, suppliers, and customers. Moore’s Law increases in storage capacity and processing power can no longer keep up with the pace of data expansion, yet how companies structure and analyze their data ultimately will impact their ability to compete. Unstructured, disconnected data is useless. Graph databases will rapidly jump from niche use cases to a transformative IT technology as they enable turning the data you collect into actionable insights. Data will become the single most differentiating asset for your organization.
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graphgrid
Published By: Embarcadero     Published Date: Jul 23, 2015
Whether you’re working with relational data, schema-less (NoSQL) data, or model metadata, you need a data architecture that can actively leverage information assets for business value. The most valuable data has high quality, business context, and visibility across the organization. Check out this must-read eBook for essential insights on important data architecture topics.
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Embarcadero
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: CMMI Institute     Published Date: Sep 03, 2014
To drive strategic insights that lead to competitive advantage, businesses must make the best and smartest use of today’s vast amount of data. To accomplish this, organizations need to apply a collaborative approach to optimizing their data assets. For organizations that seek to evaluate and improve their data management practices, CMMI® Institute has developed the Data Management Maturity (DMM)? model to bridge the perspective gap between business and IT. Download the white paper Why is Measurement of Data Management Maturity Important? to enable you to: - Empower your executives to make better and faster decisions using a strategic view of their data. - Achieve the elusive alignment and agreement between the business and IT - Create a clear path to increasing capabilities
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white paper, enterprise data management, data model, data modeling, data maturity model, cmmi institute
    
CMMI Institute
Published By: AT&T     Published Date: Sep 11, 2014
The age of Big Data is upon us. Storage costs are going down, and data analytics is becoming more capable and more user-friendly. Even your auto mechanic will be storing a petabyte of data soon. Big Data will give businesses new insights and help improve operations. With these new tools come questions about how to use them. But your mechanic knows more about fixing a transmission than developing a Hadoop cluster, and similar concerns hold true for larger enterprises. Businesses everywhere are looking for guidance.
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AT&T
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: Trillium Software     Published Date: Apr 10, 2017
For the 11th consecutive year, the Gartner Magic Quadrant for Data Quality Tools1 research report positions Trillium Software as a leader in the Data Quality Software industry. Data Quality is vital to ensuring trust in your data-driven, decision making business processes. Confidence is the result of a well thought out and executed data quality management strategy and is critical to remaining competitive in a rapidly and ever-changing business world. The 2016 Gartner Magic Quadrant for Data Quality Tools report is a valuable reference, providing the latest insights into the strengths and cautions of leading vendors. Access the report to learn how a leading data quality solution can help you achieve your long-term strategic objectives.
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Trillium Software
Published By: Reltio     Published Date: Feb 12, 2016
Reltio delivers reliable data, relevant insights and recommended actions so companies can be right faster. Reltio Cloud combines data-driven applications with modern data management for better planning, customer engagement and risk management. IT streamlines data management for a complete view across all sources and formats at scale, while sales, marketing and compliance teams use data-driven applications to predict, collaborate and respond to opportunities in real-time. Companies of all sizes, including leading Fortune 500 companies in healthcare and life sciences, distribution and retail rely on Reltio.
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Reltio
Published By: Looker     Published Date: Sep 27, 2017
Creating metrics to measure the success or failure of your business may seem simple, but there are many avoidable mistakes that business leaders make every day. Many leaders end up focusing on “vanity metrics”, which might make the business look healthy, but do not actually give you insights into what is going on. And worst case, they are masking larger issues that you need to know and should be addressing. In this report, learn from other data-driven businesses how to avoid vanity metrics and focus on metrics that matter.
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Looker
Published By: IDERA     Published Date: Nov 07, 2017
Data modeling is all about data definition but has a much wider impact on the data of your organization. Quality data definition impacts how data is produced and directly impacts how the data is or will be used throughout an organization. That means that we must proactively govern the process of how we define data, to establish a common understanding across the team. In this whitepaper, Robert Seiner describes how data modeling is a form of data governance and provides insights on the three actions of governing data.
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IDERA
Published By: Alteryx     Published Date: May 24, 2017
Spreadsheets are a mainstay in almost every organization. They are a great way to calculate and manipulate numeric data to make decisions. Unfortunately, as organizations grow, so does the data, and relying on spreadsheet-based tools like Excel for heavy data preparation, blending and analysis can be cumbersome and unreliable. Alteryx, Inc. is a leader in self-service data analytics and provides analysts with the ability to easily prep, blend, and analyze all data using a repeatable workflow, then deploy and share analytics at scale for deeper insights in hours, not weeks. This paper highlights how transitioning from a spreadsheet-based environment to an Alteryx workflow approach can help analyst better understand their data, improve consistency, and operationalize analytics through a flexible deployment and consumption environment.
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Alteryx
Published By: Erwin     Published Date: Sep 13, 2018
Do you know what data you have, where it is and how to wring all the possible value from it? By harmonizing your data management and data governance efforts, you can accelerate your time to data preparation, data visibility and data-driven insights. Then you’ll know how to get the results you need.
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Erwin
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: 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: 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: Data Blueprint     Published Date: Jul 15, 2013
The role of the chief data officer (CDO) is relatively new across the organizational landscape – 70% of current CDO positions were created in the last year alone! The past decade has seen a combination of events, forcing organizations to consider this increasingly important role.
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Data Blueprint
Published By: HERE Technologies     Published Date: Jan 16, 2019
With content plentiful and audience attention hard to attract—let alone retain—advertising has to go beyond simple personalization. Discover how HERE is bridging the gap, adding context to our view of the consumer using location-based insights that span the digital and physical worlds. So, you can learn not only who the audience is, but precisely where they are—and why. Learn more in the HERE eBook.
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location data, ad tech, location targeting
    
HERE Technologies
Published By: HERE Technologies     Published Date: Jan 16, 2019
Audience segmentation is key for successful ad campaigns. Without it, a brand is flying blind – wasting spend and resources. However, the good news is that increasingly sophisticated technology makes it possible for brands to gain a deeper understanding of their target audiences – and how to reach them. This is especially true of location intelligence-driven advertising which can give more timely and complete insights into audiences than ever before. As one of the world’s leading location platforms in 2018, HERE Technologies shares insights and solutions to buying location data for better audience segmentation. Find out about the challenges and questions to ask when buying location data and download the Buyers Guide for Marketers.
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location data, ad tech, location targeting
    
HERE Technologies
Published By: Lenovo and Intel®     Published Date: Jan 08, 2019
If you are trying to process, understand, and benefit from "big data," you need SAP® HANA®. In-memory database Process data at extreme speeds Real-time analytics and insights If you want to make sure you have access to your data for insights, whenever and wherever you need them, then SAP HANA on Lenovo's future-defined infrastructure—powered by the Intel® Xeon® Platinum processor—delivers what you need. Get the details on everything you need to know about the value of SAP HANA, why SAP chose Lenovo for their own HANA installation, and how Lenovo can help your organization today.
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sap hana, lenovo, intel, big data, database, analytics, insights
    
Lenovo and Intel®
Published By: Workplace by Facebook     Published Date: Dec 21, 2018
We believe people change organizations. So, we built Workplace by Facebook to empower them. Our mission is to unlock human potential by giving the world a place to work together. We do it by combining next-generation technology and easy-to use features to transform communications, culture, and workflows inside organizations of all shapes, sizes, and industries. Industries like retail. In this playbook, we’ll explore the new consumer expectations shaping the future of retail in North America. You’ll discover why great brand experiences for your customers start with great work experiences for your employees. Download this whitepaper now to learn more about the benefits of customer-centric collaboration tools like Workplace by Facebook. Then you’ll be ready to take the next step on your digital transformation journey.
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Workplace by Facebook
Published By: TIBCO Software GmbH     Published Date: Jan 15, 2019
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 no need to rework faulty products. To satisfy the customer demand behind this trend, manufacturers must move quickly to new production models. Quality assurance is the key area that IT must support. At the same time, the traceability of products becomes central to compliance as well as quality. Traceability can be achieved by interconnecting data sources across the factory, analyzing historical and streaming data for insights, and taking immediate action to control the entire end-to-end process. Doing so can lead to noticeable cost reductions, and gains in efficiency, process reliability, and speed of new product delivery. Additionally, analytics helps manufacturers find the best setups for machinery.
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TIBCO Software GmbH
Published By: TIBCO Software GmbH     Published Date: Jan 22, 2019
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution. Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze. Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform. Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing: • Reduced downtime • Minimized surplus and defects • Deep insights • End-to-end real-time visibility
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TIBCO Software GmbH
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