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Published By: VoltDB     Published Date: Jul 09, 2015
What is fast data? It's data in motion, and it creates Big Data. But handling it requires a radically different approach. Download the Fast Data Stack white paper from VoltDB. Learn how to build fast data applications with an in-memory solution that’s powerful enough for real-time stateful operations.
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data, data management, data stack, bug data, voltdb, database, nosql
    
VoltDB
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: Trillium Software     Published Date: Mar 29, 2016
We are living in a new age in which your business success depends on access to trusted data across more systems and more users faster than ever before. However, your business information is often incomplete, filled with errors, and beyond the reach of people who need it. Whether you’re responsible for technology or information strategy, you need to enable your business to have real-time access to reliable information. Otherwise, your company will be left behind. Download Trillium’s whitepaper, “How to Succeed in the New Age of Data Quality”, to learn how you can create a successful data quality strategy.
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Trillium Software
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: Experian     Published Date: May 17, 2016
Every year, Experian Data Quality conducts a study to look at the global trends in data quality. This year, research findings reveal how data practitioners are leveraging and managing data to generate actionable insight, and how proper data management is becoming an organization-wide imperative. This study polled more than 1,400 people across eight countries globally from a variety of roles and departments. Respondents were chosen based on their visibility into their orgazation's customer data management practices. Read through our research report to learn: - The changes in channel usage over the last 12 months - Expected changes in big data and data management initiatives - Multi-industry benchmarks, comparisons, and challenges in data quality - And more! Our annual global benchmark report takes a close look at the data quality and data management initiatives driving today's businesses. See where you line up and where you can improve.
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Experian
Published By: Experian     Published Date: Mar 30, 2017
Businesses today recognize the importance of the data they hold, but a general lack of trust in the quality of their data prevents them from achieving strategic business objectives. Nearly half of organizations globally say that a lack of trust in their data contributes to increased risk of non-compliance and regulatory penalties (52%) and a downturn in customer loyalty (51%). To be of value to organizations, data needs to be trustworthy. In this report, you will read about the findings from this unique study, including: · How data powers business opportunities · Why trusted data is essential for performance · Challenges that affect data quality · The current state of data management practices · Upcoming data-related projects in 2017
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Experian
Published By: Experian     Published Date: Mar 12, 2018
Data is quickly becoming the currency of the emerging digital economy. As digital transformation efforts proliferate and become commonplace, data will take center stage as a critical driver of these initiatives. Organizations that are able to mobilize their data assets to power critical business initiatives will see a distinct advantage in the years to come. In fact, a majority of C-level executives (87%) believe that data has greatly disrupted their organization’s operations over the last 12 months. As the reliance on data deepens, the need for trustworthy and reliable data assets will become increasingly important. This year’s global study highlights several important issues and opportunities throughout the data management and data quality spaces. By discussing the latest advancements and challenges within our industry, we hope to empower all organizations to better leverage their data and to thrive in the digital economy.
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Experian
Published By: Experian     Published Date: Mar 12, 2018
Data is quickly becoming the currency of the emerging digital economy. As digital transformation efforts proliferate and become commonplace, data will take center stage as a critical driver of these initiatives. Organizations that are able to mobilize their data assets to power critical business initiatives will see a distinct advantage in the years to come. In fact, a majority of C-level executives (87%) believe that data has greatly disrupted their organization’s operations over the last 12 months. As the reliance on data deepens, the need for trustworthy and reliable data assets will become increasingly important. This year’s global study highlights several important issues and opportunities throughout the data management and data quality spaces. By discussing the latest advancements and challenges within our industry, we hope to empower all organizations to better leverage their data and to thrive in the digital economy.
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Experian
Published By: Experian     Published Date: Jun 01, 2018
Better data insight is the key to becoming a more informed, profitable company. Download this white paper to understand: -How to overcome challenges you may have with your data management strategy -What improvements you should make that will make the biggest impact -The importance of being proactive rather than reactive to data quality issues
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Experian
Published By: Ontotext     Published Date: Dec 21, 2015
Learn how semantic technologies make any content intelligent and turn it into revenue for your publishing business There is a smarter, cost-effective way for publishers to create, maintain and reuse content assets with higher accuracy. It is called dynamic semantic publishing. Putting Semantic Technologies at Work for the Publishing Industry An efficient blend of semantic technologies, dynamic semantic publishing enables powerful experiences when it comes to publishers’ main stock of trade: processing and representing information.
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Ontotext
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: Reltio     Published Date: Aug 11, 2017
"Forrester's research uncovered a market in which Reltio [and other companies] lead the pack,” the Forrester Wave Master Data Management, 2016 states. "Leaders demonstrated extensive and MDM capabilities for sophisticated master data scenarios, large complex ecosystems, and data governance to deliver enterprise-scale business value.”
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Reltio
Published By: Reltio     Published Date: May 21, 2018
Effective May 25, 2018, General Data Protection Regulation (GDPR) will represent the most rigorous data protection regulation ever. Complying is not optional, and the penalties are very high. As companies scurry for total compliance, it makes sense to pause, assess, and use this opportunity not only for compliance but for managing customer data efficiently and gainfully. Reltio proposes ten simple steps to ensure your data management strategy is ready for GDPR, not just for assured compliance but going beyond and enabling better customer experiences and building business competence.
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Reltio
Published By: Reltio     Published Date: May 22, 2018
"Forrester's research uncovered a market in which Reltio [and other companies] lead the pack,” the Forrester Wave Master Data Management states. "Leaders demonstrated extensive and MDM capabilities for sophisticated master data scenarios, large complex ecosystems, and data governance to deliver enterprise-scale business value.” Reltio executes the vision for next-generation MDM by converging trusted data management with business insight solutions at scale and in the cloud. Machine learning and graph technology capabilities enable a contextual data model while also maintaining temporal and lineage changes of the master data.
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Reltio
Published By: Reltio     Published Date: Nov 16, 2018
Modern Master Data Management (MDM) is more than an extension of your data governance strategy. See how Reltio is taking MDM to the next level with its data platforms in AWS and Google Cloud.
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Reltio
Published By: Reltio     Published Date: Nov 16, 2018
Big data is growing faster than the capabilities available to manage and analyze it. Get this vendor comparison to learn how a modern master data management platform will help you to achieve better outcomes.
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Reltio
Published By: Reltio     Published Date: Nov 16, 2018
Explore this 31-criteria, Forrester Wave Report on MDM platforms and vendors. You'll discover an evaluation of 12 vendors including leader Reltio with modern Master Data Management.
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Reltio
Published By: Silwood Technology     Published Date: Mar 02, 2016
Ever since organisations started to implement packaged software solutions to solve business problems and streamline their processes there has been a need to access their data for the purposes of reporting and analytics, integration, governance, master data and more. Information Management projects such as these rely on data professionals being able to understand the underlying data models for these packages in order to be able to answer the critical question “Where’s the data?”. Without this knowledge it is impossible to ensure accuracy of data or timely delivery of projects. In addition the lack of discovery tools designed to meet this challenge has meant that performing this task has commonly been frustrating, time-consuming and fraught with risk. This white paper offers insight into why the traditional methods are not effective and how an innovative software product from Silwood Technology provides a faster and more effective approach to solving the problem.
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Silwood Technology
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: 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: Alation     Published Date: Mar 15, 2016
curation (noun): The act of organizing and maintaining a collection (such as artworks, artifacts, or data). Data curation is emerging as a technique to support data governance, especially in data-driven organizations. As self-service data visualization tools have taken off, sharing the nuances and best practices of how to use data becomes ever more critical. Analysts at companies from eBay to Safeway and Square are scaling their data knowledge through curation techniques. What are the 4 steps to successful data curation? Find out here:
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data stewardship, self-service analytics, data curation, data governance
    
Alation
Published By: Alation     Published Date: Mar 26, 2018
When analysts and data scientists have access to data governance policies and best practices directly within the flow of their analysis, the result is both more consistent compliance and more broadly adopted best practices. With the combination of Tableau and Alation, organizations can not only balance the demands of agility and governance, they can actually optimize for both at the same time. We call this Governance for Insight. Learn more about how Tableau users can have the best of worlds - agility and governance. Read Enabling Governance for Insight: Trust in Data with Tableau and Alation’s Data Catalogs. Register on the right to access a complimentary copy of this joint white paper from Tableau and Alation.
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Alation
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