data sources

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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: 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: 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: MapR Technologies     Published Date: Mar 29, 2016
Add Big Data Technologies to Get More Value from Your Stack Taking advantage of big data starts with understanding how to optimize and augment your existing infrastructure. Relational databases have endured for a reason – they fit well with the types of data that organizations use to run their business. These types of data in business applications such as ERP, CRM, EPM, etc., are not fundamentally changing, which suggests that relational databases will continue to play a foundational role in enterprise architectures for the foreseeable future. One area where emerging technologies can complement relational database technologies is big data. With the rapidly growing volumes of data, along with the many new sources of data, organizations look for ways to relieve pressure from their existing systems. That’s where Hadoop and NoSQL come in.
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MapR Technologies
Published By: Cambridge Semantics     Published Date: May 11, 2016
With the explosive growth of Big Data, IT professionals find their time and resources squeezed between managing increasingly large and diverse siloed data stores and increased user demands for timely, accurate data. The graph-based ANZO Smart Data Manager is built to relieve these burdens by automating the process of managing, cataloging and governing data at enterprise scale and security. Anzo Smart Data Manager allows companies to truly understand their data ecosystems and leverage the metadata within it.
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Cambridge Semantics
Published By: MemSQL     Published Date: Jun 25, 2014
Emerging business innovations focused on realizing quick business value on new and growing data sources require “hybrid transactional and analytical processing” (HTAP), the notion of performing analysis on data directly in an operational data store. While this is not a new idea, Gartner reports that the potential for HTAP has not been fully realized due to technology limitations and inertia in IT departments. MemSQL offers a unique combination of performance, flexibility, and ease of use that allows companies to implement HTAP to power their business applications.
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MemSQL
Published By: Melissa Data     Published Date: Jan 18, 2018
Maintaining high quality data is essential for operational efficiency, meaningful analytics and good long-term customer relationships. But, when dealing with multiple sources of data, data quality becomes complex, so you need to know when you should build a custom data quality tools over canned solutions. To answer this question, it is important to understand the difference between rules-based data quality, where internal subject matter expertise is necessary – and active data quality, where different domain expertise and resources are required.
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Melissa Data
Published By: CapTech     Published Date: May 26, 2015
Big Data is the future of business. According to CloudTweaks.com, as much as 2.5 quintillion bytes of data are produced each day, with most of this data being captured by Big Data. With its ability to transfer all data sources all into one centralized place, Big Data provides opportunities, clearer visions, customer conversations and transactions. However, with the dazzling big promise of Big Data comes a potentially huge letdown. If this vast pool of information resources is not accessible or usable, it becomes useless. This paper examines strategies for building the most value into your Big Data system by enabling process controls to effectively mine, access and secure Big Data.
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big data, captech, data, data management, nosql
    
CapTech
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: Reltio     Published Date: Jan 20, 2017
If you invested in master data management (MDM), you are part of an elite association of those who have been able to afford the time, effort and resources to deploy what has characteristically been a tool, and discipline reserved for only the largest enterprises. Feedback from top industry analysts and companies that transitioned from legacy MDM to modern data management platforms, led to the compilation of a list of 10 warning signs you can use as a handy guide. If one or more of these signs get your attention, it warrants a serious conversation with your current provider about these issues, and how they compare to modern offerings available today.
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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: CloverETL     Published Date: Nov 24, 2017
The volume of data is increasing by 40% per year (Source: IDC). In addition, the structure and quality of data differs vastly with a growing number of data sources. More agile ways of working with data are required. This whitepaper discusses the vast options available for managing and storing data using data architectures, and offers use cases for each architecture. Furthermore, the whitepaper explores the benefits, drawbacks and challenges of each data architecture and commonly used practices for building these architectures.
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CloverETL
Published By: Syncsort     Published Date: Jan 04, 2018
The term Big Data doesn’t seem quite “big enough” anymore to properly describe the vast over-abundance of data available to organizations today. As the volume and variety of Big Data sources continue to grow, the level of trust in that data remains troublingly low. Read on and discover how a strong focus on data quality spanning the people, processes and technology of your organization will help keep your data lake pristine.
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Syncsort
Published By: Zoomdata     Published Date: Apr 11, 2018
How do you imagine data? If you’re thinking about it in terms of uniform records and databases, it’s time to make a brain update. Back in the day, analytical engines were limited, so our perception of what could be considered data was, too. Today, the big data renaissance has begun, and actually, more of the data exists outside of databases than inside them, plus, EVERYTHING is data. We’re going to help you discover how business intelligence and data sources of today have changed, and as a result, so has our approach to analyzing data. An eBook on this very topic is waiting for you—all it takes is the click of a button.
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Zoomdata
Published By: TopQuadrant     Published Date: Jul 18, 2016
With information streaming in from more varied sources and at a faster pace than ever before, organizations are having an increasingly difficult time deriving accurate meaning from their data. Data governance systems that were once able to organize and process enterprise information are becoming too slow and limited.   Semantic information management makes it easier to reconcile data from different sources by compiling and organizing information about that data, its metadata. By connecting all kinds of data and metadata in a more accessible way, semantic information systems empower users, data stewards and analysts to unlock and use the true meaning and value of their organization’s data.     Learn more about the challenges in the evolving data landscape and how a semantic approach can help.
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TopQuadrant
Published By: TopQuadrant     Published Date: Aug 01, 2016
With information streaming in from more varied sources and at a faster pace than ever before, organizations are having an increasingly difficult time deriving accurate meaning from their data. Data governance systems that were once able to organize and process enterprise information are becoming too slow and limited. Semantic information management makes it easier to reconcile data from different sources by compiling and organizing information about that data, its metadata. By connecting all kinds of data and metadata in a more accessible way, semantic information systems empower users, data stewards and analysts to unlock and use the true meaning and value of their organization’s data. Learn more about the challenges in the evolving data landscape and how a semantic approach can help.
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TopQuadrant
Published By: TopQuadrant     Published Date: Apr 16, 2013
TopBraid Insight provides an ‘out-of-the-box’ Logical Data Warehouse that allows an agile, extensible approach to querying data from diverse data sources. This white paper describes the approach as applied to the Life Sciences industry.
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TopQuadrant
Published By: Here Technologies     Published Date: Sep 26, 2018
Adsquare offers brands insights into customer behaviours and footfall to underpin digital marketing campaigns. Using a detailed brief of the audience the brand wishes to reach, Adsquare gathers data from a range of mobile, online and offline sources. This rich data gives a brand a stronger opportunity to create relevant campaigns for their audiences. It is critical to adsquare’s success that its data sources are reliable. As the world’s leading location platform in 2018 (Source: Ovum and Counterpoint Research annual indexes) HERE is building and sharing real-time location intelligence with adsquare which reveals patterns to show how and why customers make transactions in specific places. and why customers make transactions in specific places.
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Here Technologies
Published By: Here Technologies     Published Date: Sep 26, 2018
Get higher quality, more accurate location data – and a safer, more profitable fleet – by choosing the right location services provider. The true value of a location platform comes from bringing together multiple data sources and presenting them in a meaningful way. Using a platform approach, you can help customers differentiate their service, increase margins and increase safety. So, in this guide, we cover the four key considerations for choosing a mapping and location service platform to ensure a high quality, accurate mapping service for you and your customers. Download the eBook
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Here Technologies
Published By: Carbonite     Published Date: Oct 10, 2018
Backup and high availability are both essential forms of protection that fulfill different roles within a data protection strategy. So which type of protection is right for different systems? According to recent analyst reports, experts recommend a blended approach that aligns data protection with type of data.1 By aligning data protection with data urgency, businesses can ensure higher levels of resiliency and reduce demands on internal resources.
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Carbonite
Published By: Juniper Networks     Published Date: Oct 02, 2018
As customers demand and expect more of a digitized experience, the scale and volume of secure data that’s being transmitted across the network is increasing exponentially. At the same time, across the APAC region high digital connectivity, contrasted with low cybersecurity awareness, growing cross-border data transfers and weak regulations have made this data a global target. The growth in the “as-a-service” nature of the cybercrime marketplace is also fueling an increase in the number of traditional crime groups and individuals drawn into cyber offending. New sources of vulnerability from mobile, BYOD, CYOD, web-services and IoT devices are further broadening the cyber threat landscape with ever-more sophisticated forms of malware and DDoS attacks. Download the IDC Report to get some tips on how to stay protected against cybercrime.
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Juniper Networks
Published By: Group M_IBM Q418     Published Date: Oct 02, 2018
Across enterprises of all kinds, data is multiplying rapidly in both quantity and variety. Across multi-cloud environments, new sources are exponentially increasing the growing stream of information, including the Internet of Things, social media, mobile devices, virtual reality implementations and optical tracking.
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Group M_IBM Q418
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