define data

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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: 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: Embarcadero     Published Date: Oct 21, 2014
Metadata defines the structure of data in files and databases, providing detailed information about entities and objects. In this white paper, Dr. Robin Bloor and Rebecca Jowiak of The Bloor Group discuss the value of metadata and the importance of organizing it well, which enables you to: - Collaborate on metadata across your organization - Manage disparate data sources and definitions - Establish an enterprise glossary of business definitions and data elements - Improve communication between teams
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data, data management, enterprise data management, enterprise information management, metadata, robin bloor, rebecca jozwiak, embarcadero
    
Embarcadero
Published By: Embarcadero     Published Date: Jan 23, 2015
There are multiple considerations for collaborating on metadata within an organization, and you need a good metadata strategy to define and manage the right processes for a successful implementation. In this white paper, David Loshin describes how to enhance enterprise knowledge sharing by using collaborative metadata for structure, content, and semantics.
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data, data management, metadata, enterprise information management, data modeling, embarcadero
    
Embarcadero
Published By: VoltDB     Published Date: Feb 12, 2016
The need for fast data applications is growing rapidly, driven by the IoT, the surge in machine-to-machine (M2M) data, global mobile device proliferation, and the monetization of SaaS platforms. So how do you combine real-time, streaming analytics with real-time decisions in an architecture that’s reliable, scalable, and simple? In this report, Ryan Betts and John Hugg from VoltDB examine ways to develop apps for fast data, using pre-defined patterns. These patterns are general enough to suit both the do-it-yourself, hybrid batch/streaming approach, as well as the simpler, proven in-memory approach available with certain fast database offerings.
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VoltDB
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: 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: Dataiku     Published Date: Feb 01, 2018
A proof of concept (POC) is a popular way for businesses to evaluate the viability of a system, product, or service to ensure it meets specific needs or sets of predefined requirements. But what does running a POC mean in practice specifically for data science? POCs should prove not just that a solution solves one particular, specific problem, but that the solution in question will provide widespread value to the company: that it's capable of bringing a data-driven perspective to a range of the business's strategic objectives. Get the 7 steps to running an efficient POC in this white paper.
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Dataiku
Published By: Dataiku     Published Date: Feb 19, 2018
A proof of concept (POC) is a popular way for businesses to evaluate the viability of a system, product, or service to ensure it meets specific needs or sets of predefined requirements. But what does running a POC mean in practice specifically for data science? POCs should prove not just that a solution solves one particular, specific problem, but that the solution in question will provide widespread value to the company: that it's capable of bringing a data-driven perspective to a range of the business's strategic objectives. Get the 7 steps to running an efficient POC in this white paper.
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Dataiku
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: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
Powerful IT doesn’t have to be complicated. Hyperconvergence puts your entire virtualized infrastructure and advanced data services into one integrated powerhouse. Deploy HCI on an intelligent fabric that can scale with your business and you can hyperconverge the entire IT stack. This guide will help you: Understand the basic tenets of hyperconvergence and the software-defined data center; Solve for common virtualization roadblocks; Identify 3 things modern organizations want from IT; Apply 7 hyperconverged tactics to your existing infrastructure now.
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Hewlett Packard Enterprise
Published By: Comcast Business     Published Date: Feb 06, 2019
The quick-service restaurant industry continues to be a favorite among consumers who look to the sector for a wide variety of food served quickly and at a low price. The speed and efficiency of QSRs, which include the emergent “fast casual” restaurants, match today’s on-the-go lifestyle of consumers across all ages who often are too busy to cook at home. That said, consumers expect their dining experience at a QSR to be comfortable with conveniences ranging from WiFi connectivity to ordering kiosks and dining area entertainment on large screens or even tableside tablets. They expect the information on menu boards to be accurate and up-to-date and their meal orders to be fulfilled quickly and accurately. Technology is a major enabler in meeting consumers’ expectations while simultaneously helping QSR locations increase operational efficiencies and quality of service.
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restaurants, quick-serve restaurants, qsr, fast food, convenience food, restaurant technology, qsr technology, guest experience, pos, digital entertainment, wifi, television, network, technology, digital transformation, tech future, enterprise technology, networking, sd_wan, internet
    
Comcast Business
Published By: Comcast Business     Published Date: Feb 06, 2019
Hospitality is a customer-focused industry, with a hotel brand’s reputation and ultimate success dependent on the quality of the experience of its guests. It is no surprise then, that digital transformation efforts within the hospitality sector are focused on technologies that improve the guest experience, from check-in to check-out and everything in between. Today’s travelers are digitally savvy, using their smartphones and mobile devices for a multitude of tasks. They expect a high-quality connection throughout the property and the ability to perform certain tasks from the hotel’s app, such as checking in and choosing their own room. They expect in-room entertainment beyond basic cable and in-room digital devices they can use to order food, book a massage or control the lighting, for example.
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hospitality, hospitality providers, hotel technology, motel technology, guest experience, pos, digital entertainment, wifi, hospitality technology, network, technology, digital transformation, tech future, enterprise technology, networking, sd_wan, internet, ethernet, unified communication, digital initiative
    
Comcast Business
Published By: Comcast Business     Published Date: Feb 06, 2019
Retail has been transformed by technology in multiple ways, from the way customers interact with retailers to how products are offered and acquired. Indeed, the entire shopping experience has been redefined and expanded to enable customers to purchase products anytime, anywhere, with any device, from any number of retailers. Consumers’ changing shopping behaviors and their reliance on technology enables retailers to reach a wider swath of potential buyers, moving well beyond the borders of their physical store locations to new geographies and populations. That said, retailers must understand how to use technology effectively to draw in customers and entice them to purchase, as well as help them improve their operations and enable new, innovative ways to keep customers coming back.
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retail, shopping, retailers, wifi, retail technology, network, technology, digital transformation, tech future, enterprise technology, networking, sd_wan, internet, ethernet, unified communication, digital initiative, digital first, cloud, sdn, software-defined-networking
    
Comcast Business
Published By: Comcast Business     Published Date: Feb 06, 2019
Just like your business, technology never stops advancing. Each year, there are new ways that technology can automate processes, lower costs, and enhance customer and employee satisfaction - all with the goal of increasing revenue! And while it can be difficult to change how your business works, leaving old methods behind and embracing new technology can help lead your business to more success and growth.
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network, technology, digital transformation, tech future, enterprise technology, networking, sd_wan, internet, ethernet, unified communication, digital initiative, digital first, cloud, sdn, software-defined-networking, gig speed, mobile, big data, analytics, automation
    
Comcast Business
Published By: Comcast Business     Published Date: Feb 06, 2019
The technology landscape in the financial services sector is vast, ranging from cutting-edge to mission-critical, each having an impact on the industry as a whole. Customer-facing services and back-end operations alike are seeing real benefits from innovation, including greater efficiencies and higher levels of customer satisfaction.
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network, technology, digital transformation, tech future, enterprise technology, networking, sd_wan, internet, ethernet, unified communication, digital initiative, digital first, cloud, sdn, software-defined-networking, gig speed, mobile, big data, analytics, automation
    
Comcast Business
Published By: Comcast Business     Published Date: Feb 06, 2019
The rate at which technology is evolving is increasing almost exponentially. In the business sector, hardware has given way to software-defined everything, while many on-premises technologies are now offered as a service. Much of the advances in technology over the last few years have been the direct result of the growing ubiquity of the cloud and faster connectivity speeds, both of which have enabled companies to adopt digital transformation technologies to help them work smarter and more efficiently.
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network, technology, digital transformation, tech future, enterprise technology, networking, sd_wan, internet, ethernet, unified communication, digital initiative, digital first, cloud, sdn, software-defined-networking, gig speed, mobile, big data, analytics, automation
    
Comcast Business
Published By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications, database development
    
SAP
Published By: HPE Intel     Published Date: Jan 11, 2016
A famous architect once said that the origin of architecture was defined by the first time “two bricks were put together well.” And the more bricks you have, the more important putting them together well becomes. The same holds true in our data centers. The architecture of our compute, storage and network devices has always been important, but as the demands on our IT infrastructures grow, and we add more “bricks,” the architecture becomes more critical.
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HPE Intel
Published By: Dell     Published Date: Jul 08, 2016
Organizations looking to implement desktop and app virtualization traditionally play a guessing game where storage is concerned. When considering local and physical storage, determining what would be necessary for the virtualized world is difficult and can be overwhelming. This is especially true when determining how virtualizing desktops will impact the storage architecture. Organizations risk over sizing their environment thereby wasting CapEx, or under-sizing and potentially ruining the user experience. Software-defined storage solutions, such as VMware Virtual SAN, provide simplified solutions with high performance data stores that offer fine-grained scalability with linearly-predictable performance as demand grows. Dell’s validated and certified desktop virtualization solutions incorporate vSphere and Virtual SAN, and provide a complete end-to-end solution that allows companies to grow and expand without large capital investments in SAN hardware.
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technology, best practices, data, virtualization, storage, data, business technology
    
Dell
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