data report

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Published By: Oracle     Published Date: Sep 21, 2016
This digibook contains a step-by-step guide to overcoming the new challenges of raised expectations, big data, and globalization, with case studies and examples of how smart CFOs are redefining reporting.
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Oracle
Published By: Red Hat     Published Date: Sep 25, 2014
As a strategic partner in your business, you face increasing demands from your line-of-business leaders for new functionality and advanced capabilities, which you must deliver with a constrained IT budget. What could you do to meet these expectations and add value to the business if you could contain costs, increase operational efficiency, and do more with less? You need to overcome several challenges. The cost of software licensing management is rising as a result of maintaining proprietary platforms or legacy technology, making it difficult to modernize your datacenter and migrate to more cost-effective solutions. You’re likely burdened by regulatory compliance mandates, which create enforcement, reporting, and auditing expenses. And, like 67% of IT organizations, your budget is probably shrinking. Red Hat can help. Red Hat® Enterprise Linux® gives you the high-value subscription model, built-in governance processes, and simplified migration path you need to aggressively lower your
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increased demands, functionality, software licensing management, proprietary platforms, legacy technology, datacenter, it organization, it management, data management
    
Red Hat
Published By: NetApp     Published Date: Sep 22, 2014
The NetApp EF series of all-flash arrays are designed specifically for database-driven environments demanding maximum performance, reliability, and availability. This ESG Lab Report documents the real world performance, reliability, availability, and serviceability of NetApp EF-Series flash arrays in Oracle database environments. A combination of hands on testing by ESG Lab and audited in-house performance testing executed by NetApp were used to create this report. In this report, you’ll learn how ESG validated NetApp’s EF-550 flash array performance of over 400,000 IOPS with sub-millisecond latency, while maintaining 6 nine’s availability.
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flash arrays, performance-driven databases, enterprise storage, database environment, serviceability, real world performance
    
NetApp
Published By: NetApp     Published Date: Sep 22, 2014
NetApp Flash Pool is a storage cache option within the NetApp Virtual Storage Tier product family, available for NetApp FAS storage systems. A Flash Pool configures solid state drives (SSDs) and hard disk drives (HDDs) into a single storage pool, known as an “aggregate” in NetApp parlance, with the SSDs providing a fast response time cache for volumes that are provisioned on the Flash Pool aggregate. In this lab evaluation, NetApp commissioned Demartek to evaluate the effectiveness of Flash Pool with different types and numbers of hard disk drives using an online transaction processing (OLTP) database workload, and to evaluate the performance of Flash Pool in a clustered Data ONTAP environment during a cluster storage node failover scenario. In the report, you’ll dis cover how Demartek test engineers documented a 283% gain in IOPS and a reduction in latency by a factor of 66x after incorporating NetApp Flash Pool technology.
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flash pool, fas storage systems, ssd, online transaction processing, cluster storage
    
NetApp
Published By: MarkLogic     Published Date: Jun 19, 2017
Integrate your data silos to finally navigate the data maze. This comprehensive white paper addresses a key element in any GRC program: regulatory compliance. Download this paper to learn about the costs, current practices, and associated risks. We’ll also recommend a technologically-enabled approach and highlight its main business benefits for financial services, insurance, and energy companies. Overview Executive Summary Compliance Requirements A Recommended Approach Business Benefits Regulatory Compliance Solution Architecture Related Materials
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banking, financial services, data management, silos, data strategy, transparency, data governance, regulation, data architecture, compliance, reporting, energy, insurance
    
MarkLogic
Published By: MarkLogic     Published Date: Jun 19, 2017
There is opportunity in the ongoing turbulence throughout the financial industry; however, regulatory and compliance challenges absorb resources and distract focus away from growth. Download white paper to learn about a smart approach to data and innovative tools that build resilience into a business looking to not just weather the storm, but seize the advantage. Overview: - Executive Summary - Challenges of Financial Markets Today - The Need for a 360-View of Data - How to Deliver: Increased Transparency Adapt to Evolving Regulations Improve Compliance and Lower Cost - Solution Architecture for Regulatory Reporting - Case Study: Adapting to Regulatory Complexity "Disparate systems led to frequent cycles spent correcting errors within the data”.
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banking, financial services, data management, silos, data strategy, transparency, data governance, regulation, data architecture, compliance, reporting
    
MarkLogic
Published By: MarkLogic     Published Date: Jun 21, 2017
Remember Y2K – the IT “problem” that should have brought businesses to a screeching half? Despite the hype, the preparation led to widely documented business benefits and uncovered new opportunities that transformed organizations worldwide. Similarly in today’s highly regulated Financial Services industry, enabling GRC by integrating data from silos can be the driver for future business use cases like machine learning and anti-fraud detection services. GRC can be your catalyst for new opportunities. Listen in as our panel of financial services experts discuss the keys to reinventing your data strategy. We’ll cover: How to align your GRC strategy with a business transformation agenda How to ensure your organization’s approach to data management isn’t just a one-off solution, but a comprehensive one adaptable to changing regulations How to navigate the increasing regulatory demands for granular data security How to turn your compliance spend into new opportunities to earn revenue
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banking, financial services, data management, silos, data strategy, transparency, data governance, regulation, data architecture, compliance, reporting, business transformation, fraud, digital transformation
    
MarkLogic
Published By: MarkLogic     Published Date: Jun 21, 2017
Global financial organizations are facing increasing demands from the business for more granularity, transparency, reporting and security. If you’re on the IT side, you know this adds a different set of ‘mores’ to the equation: More duplication, delays, and people. What’s the net-net? More cost and more risk. You can balance the scales to satisfy those demands. And it starts with thinking differently about data management. Our financial services technology experts will explore the implications of governance, risk and compliance (GRC) imperatives. You’ll learn: • Why data is at the heart of an effective and dynamic GRC strategy • Why technological capabilities used to enable standard GRC programs can reduce transparency and prevent you from gaining a holistic view of your data • A new approach to data can provide the business with complete transparency • Review a sample regulatory reporting architecture Stop burning time on tooling — and start building a dynamic GRC strategy that can
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banking, financial services, data management, silos, data strategy, transparency, data governance, regulation, data architecture, compliance, reporting
    
MarkLogic
Published By: K2     Published Date: Aug 24, 2015
This complementary template focuses on the eight key areas for business process automation success to help you evaluate the quality of the platforms you are considering – and to ensure that the system you choose is agile and flexible enough to meet your business needs. WORKFLOW TOOLS AND FEATURES FORMS INTEGRATION AND DATA SECURITY MOBILE USER AND RUN-TIME EXPERIENCE REPORTING, ANALYTICS AND MONITORING MAINTENANCE/SUPPORT/HELP DOCUMENTATION
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K2
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Business users want the power of analytics—but analytics can only be as good as the data. The biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation. The increasing volume, variety, and velocity of data is putting pressure on organizations to rethink traditional methods of preparing data for reporting, analysis, and sharing. Download this white paper to find out how you can improve your data preparation for business analytics.
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Waterline Data & Research Partners
Published By: Datawatch     Published Date: Feb 03, 2016
Some companies estimate that up to 80 percent of their analysts’ time is spent on data preparation. Thorough, automated data preparation, however, can quickly transform raw information into reliable, consistent data sets ready for analysis. This report from Gartner details why information management and business analytics leaders must introduce data preparation into their big data initiatives in order to improve both the understanding of the data, and the productivity of analysts. Read the report now to learn more.
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datawatch, data preparation, data analytics, data analysis, analyst productivity, information management, business analytics, big data
    
Datawatch
Published By: IBM     Published Date: May 03, 2016
In our 33-criteria evaluation of customer analytics vendors, we identified the 11 most significant software providers in this category - adobe, agilone, alteryx, angoss, FICo, IBM, Manthan, Pitney Bowes, saP, sas, and teradata - and researched, analyzed, and scored them. this evaluation details our findings about how well each vendor fulfills our criteria and where each vendor stands in relation to each other. this report will help customer insights (CI) professionals and marketers make the right choice for their customer analytics needs.
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ibm, forrester, customer analytics, customer insights, business technology
    
IBM
Published By: IBM     Published Date: Oct 28, 2016
Watch this complimentary, on-demand 30 minute demo to see how you can: - Use HR analytics to redefine the way you manage your talent and help drive better business results. - Gain deep insights from your talent data without having to dig through mountains of reports. - Know exactly what data to explore to get the very best answers to your talent questions. - Answer your CEO's questions about the workforce in minutes, not months.
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ibm, kenexa, talent insights, talent analytics, knowledge management, business technology
    
IBM
Published By: Veritas     Published Date: May 12, 2016
This inforgraphic highlights that a ‘store everything’ hoarding culture is forming ‘databergs’: where masses of unstructured, irrelevant, unseen or unclassified data is growing daily with no notion of slowing down. They conceal a threat ‘below the waterline’ that adds significant levels of risk and cost to organisations. And this risk is rising.
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Veritas
Published By: Veritas     Published Date: May 12, 2016
In the US Databerg Report, Veritas indicates that 54% of data in US companies is "dark data", costing companies alot of money. The report advises that businesses should keep a close eye on the rapidly growing data deluge (that is, the huge influx of data), adding that many businesses already do not anticipate the contstant growth of data. As such, there are important consequences for those who ignore the growing Databerg.
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Veritas
Published By: Veritas     Published Date: May 12, 2016
The Data Genomics Index is a first-of-its-kind benchmark analysis of data stored within a typical enterprise environment. This report reveals insights into data growth, data age, and data type thereby providing organizations with the comparison standard for beginning to take action on their data. In addition to the Index, Veritas has founded the Data Genomics Project. This community of likeminded data scientists, industry experts and thought leaders will come together to surface the true nature of enterprise environments, build the data-genome that matters for information management, and share the discussion with a world struggling to solve tremendous data growth challenges.
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Veritas
Published By: IBM     Published Date: Jan 27, 2017
Analytics relies on BI, Big Data, and data discovery to provide reporting, trend what-if analysis. Analytics is transforming data into insight.
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ibm, analytics, business intelligence, data, data management
    
IBM
Published By: IBM     Published Date: Aug 23, 2017
Banks today are continuously challenged to meet rigorous regulatory requirements. They must implement strict governance programs that enable them to comply with a wide variety of regulations stemming from the financial crisis that began in 2007, including the DoddFrank Act, Basel Committee on Banking Supervision regulations, the General Data Protection Regulation (GDPR), the Revised Payment Services Directive (PSD2) and the revised Markets in Financial Instruments Directive To keep pace with regulatory changes, many banks will need to reapportion their budgets to support the development of new systems and processes. Regulators continually indicate that the banks must be able to provide, secure and deliver high-quality information that is consistent and mature.
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risk mitigation, data aggregation, risk reporting, banking
    
IBM
Published By: IBM     Published Date: Oct 17, 2017
Banks today are continuously challenged to meet rigorous regulatory requirements. They must implement strict governance programs that enable them to comply with a wide variety of regulations stemming from the financial crisis that began in 2007, including the DoddFrank Act, Basel Committee on Banking Supervision regulations, the General Data Protection Regulation (GDPR), the Revised Payment Services Directive (PSD2) and the revised Markets in Financial Instruments Directive (MiFID2). Many of these new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data
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IBM
Published By: Datastax     Published Date: May 14, 2018
"What’s In The Report? The Forrester Graph Database Vendor Landscape discusses the expanding graph uses cases, new and emerging graph solutions, the two approaches to graph, how graph databases are able to provide penetrating insights using deep data relationships, and the top 10 graph vendors in the market today Download The Report If You: -Want to know how graph databases work to provide quick, deep, actionable insights that help with everything from fraud to personalization to go-to-market acceleration, without having to write code or spend operating budget on data scientists. -Learn the new graph uses cases, including 360-degree views, fraud detection, recommendation engines, and social networking. -Learn about the top 10 graph databases and why DSE Graph continues to gain momentum with customers who like its ability to scale out in multi-data-center, multi-cloud, and hybrid environments, as well as visual operations, search, and advanced security."
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Datastax
Published By: Datastax     Published Date: May 14, 2018
"What’s In The Report? The Forrester Wave: Translytical Data Platforms, Q4 2017 report reviews companies that offer “translytical data platforms”, which Forrester defines as an “emerging technology” that delivers “faster access to business data to support various workloads and use cases.” Download the report if you want to learn: -Why Forrester named DataStax a leader among 12 companies it identifies as “the most significant translytical vendors. -What constitutes a “translytical data platform” and why translytical data platforms are so critical for enterprise data strategies today. Why performance, scale, security, and use-case support are the key differentiators."
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Datastax
Published By: Datastax     Published Date: May 14, 2018
The data management practices of old will no longer work. If you’re still trying to use a centralized approach, you are probably finding it difficult to keep up with the real-time demands of the Right-Now Economy. This special Gartner report describes the main drivers for modernizing data management — operational efficiency and analytics — and explains why balancing connecting data with collecting data will be a fundamental requirement for modern data management moving forward.
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Datastax
Published By: Datastax     Published Date: Aug 03, 2018
With DataStax Enterprise 6 (DSE 6), we upped the bar substantially for us, our partners, our customers, and our competitors. We also came out and said that DSE 6 was twice as fast as open source Apache Cassandra™, and now, we have a third-party validation of this claim. Read this benchmark report from zData to get the results of their test of DSE 6 against Cassandra, for which they ran a different series of workloads on an AWS-built cluster.
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Datastax
Published By: Datastax     Published Date: Aug 27, 2018
With DataStax Enterprise 6 (DSE 6), we upped the bar substantially for us, our partners, our customers, and our competitors. We also came out and said that DSE 6 was twice as fast as open source Apache Cassandra™, and now, we have a third-party validation of this claim. Read this benchmark report from zData to get the results of their test of DSE 6 against Cassandra, for which they ran a different series of workloads on an AWS-built cluster.
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Datastax
Published By: Datastax     Published Date: Aug 27, 2018
With DataStax Enterprise 6 (DSE 6), we upped the bar substantially for us, our partners, our customers, and our competitors. We also came out and said that DSE 6 was twice as fast as open source Apache Cassandra™, and now, we have a third-party validation of this claim. Read this benchmark report from zData to get the results of their test of DSE 6 against Cassandra, for which they ran a different series of workloads on an AWS-built cluster.
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Datastax
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