data and analytics

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Published By: TIBCO Software     Published Date: Feb 26, 2019
Digital Transformation of America's largest family controlled financial services institution with a history dating back to three generations. Learn how the role of data changed at the bank during a continued evolution of customer experience. First Citizens Bank has been using TIBCO's integration and advanced analytics technology to provide a seamless, consistent, customer self-service experience, to tackle fraud, or to provide more accurate and proactive financial services.
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financial services, digital transformation, banking, fraud
    
TIBCO Software
Published By: Hitachi Vantara     Published Date: Jan 11, 2019
Making sense of your data is one of the greatest challenges facing business today. Imagine a world where innovation and time-to-value are accelerated by AI and automation. Hitachi Vantara works at every point along the data value chain from analytics and insight, through intelligent governance to efficient, agile storage. Download this e-book to find out how to turn the business-enabling capital of the digital era into sustainable value.
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Hitachi Vantara
Published By: Seismic     Published Date: May 14, 2019
Imagine being able to walk into a meeting and say, “this is what our content has done to accelerate deals, the amount of revenue it has affected, and the ROI of our overall content strategy.” Every marketer dreams about proving ROI and the Information Age has finally made it possible for marketing teams to get concrete numbers on the success of various campaigns. But with all the data out there, how do marketers know which KPIs provide the best insight into the health and success of their marketing activities? Download the guide to learn: ? The top KPIs for improving internal marketing efficiency ? The content engagement analytics that prove value ? How to have better visibility into what content sales uses most often
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Seismic
Published By: Oracle     Published Date: Oct 20, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make bette
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make bette
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle
Published By: Workday     Published Date: Feb 01, 2019
"Are you spending more time aggregating and reconciling data than analyzing it? We uncovered the main roadblocks that are keeping finance and analytics apart, and they’ll have you rethinking the role of finance at your organization. View the infographic to get insight from more than 670 finance leaders on data intelligence."
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finance, workday, workforce technology, digital strategy
    
Workday
Published By: IBM APAC     Published Date: Oct 16, 2018
Modern AI, HPC and analytics workloads are driving an ever-growing set of data intensive challenges that can only be met with accelerated infrastructure. Designed for the AI era and architected for the modern analytics and AI workloads, Power Systems AC922 delivers unprecedented speed for the AI Era like up to 5.6 times as much bandwidth, which results from The only architecture enabling NVLink between CPUs and GPUs a variety of next-generation I/O architectures: PCIe gen4, CAPI 2.0, OpenCAPI and NVLINK. Proven simplified deep-learning deployment and AI performance
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IBM APAC
Published By: StreamSets     Published Date: Dec 05, 2018
Enterprise analytics is quickly evolving into a democratized capability where anyone can access and act on all available information, often in real-time employing advanced techniques. But the complex, dynamic and urgent nature of modern data analytics demands a new approach to data integration. This paper proposes that DataOps, the application of DevOps practices to data analytics, is the best way to overcome these challenges to create an iterative build-operate process for data movement. Read this white paper to: Understand how modern data analytics create data integration challenges due to architectural complexity, operational blindness and data drift. Learn how DevOps pillars of automation and monitoring can create higher developer productivity, operational efficiency and business confidence in data. See specific examples of DataOps functionality being applied to data integration across modern architectures.
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StreamSets
Published By: Cisco     Published Date: Jan 21, 2015
Cisco estimates that the Internet of Everything (IoE) — the networked connection of people, process, data, and things — will generate $19 trillion in Value at Stake for the private and public sectors combined between 2013 and 2022. More than 42 percent of this value — $8 trillion — will come from one of IoE’s chief enablers, the Internet of Things (IoT). Gain an Edge by Taking Analytics to the Edge!
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cisco, iot, internet, things, business, opportunity, value, automation, integration, analysis, agility, processes, ecosystem, platform
    
Cisco
Published By: IBM APAC     Published Date: Mar 19, 2018
MongoDB, one of the most popular NoSQL Open databases, helps you take advantage of exploding unstructured data with faster access to data and analytics while reducing your database cost. With the right infrastructure, you can benefit more. By running MongoDB on IBM Power systems, you can achieve: • ?Bring new apps to market faster and reduce the risk for mission-critical deployments • ?2.6x better performance for MongoDB at a much lesser cost than x86 Find out more about IBM Power Systems and MongoDB for today’s applications.
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IBM APAC
Published By: Hitachi Vantara     Published Date: Aug 02, 2018
In this book, we are going to look at the key trends driving the modernization of data infrastructure. We’ll see how organizations are adapting and flourishing in a data-driven world. For some time, headlines have been around the internet of things (IoT), big data and data analytics. While these developments are important, the reality is that you cannot take full advantage of them without modernization. We’re going to look at these trends and priorities in detail, then look at the three key drivers of modernization: governance, mobilization and analytics. We’ll also consider the technologies that make up modern data infrastructure including artificial intelligence (AI), flash storage, converged and hyperconverged platforms and software-defined infrastructures. By making sense of data, we make sense of the world. With more data than ever before, we have the tools to turn all that information into intelligent innovation and change the way the world works.
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data infrastructure, big data, internet of things
    
Hitachi Vantara
Published By: Pentaho     Published Date: Mar 08, 2016
If you’re evaluating big data integration platforms, you know that with the increasing number of tools and technologies out there, it can be difficult to separate meaningful information from the hype, and identify the right technology to solve your unique big data problem. This analyst research provides a concise overview of big data integration technologies, and reviews key things to consider when creating an integrated big data environment that blends new technologies with existing BI systems to meet your business goals. Read the Buyer’s Guide to Big Data Integration by CITO Research to learn: • What tools are most useful for working with Big Data, Hadoop, and existing transactional databases • How to create an effective “data supply chain” • How to succeed with complex data on-boarding using automation for more reliable data ingestion • The best ways to connect, transport, and transform data for data exploration, analytics and compliance
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data, buyer guide, integration, technology, platform, research, enterprise applications
    
Pentaho
Published By: Pentaho     Published Date: Apr 28, 2016
Today, the need for self-service data discovery is making data governance a charged topic. As business-driven data discovery emerges as a fundamental need, the ability to ensure that data and analytics are trustworthy and protected becomes both more difficult and more imperative. This research explains how to manage the barriers and risks of self-service and enable agile data discovery across the organization by extending existing data governance framework concepts to the data-driven and discovery-oriented business. You’ll learn: - The implications of the "freedom vs. control" paradox - How to design for iterative, "frictionless" discovery - Critical checkpoints in data discovery process where governance should be in place
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pentaho, governed data, data and analytics, governance framework, freedom vs control, frictionless discovery, networking, it management, wireless, enterprise applications, data management, business technology
    
Pentaho
Published By: Pentaho     Published Date: Apr 28, 2016
As data warehouses (DWs) and requirements for them continue to evolve, having a strategy to catch up and continuously modernize DWs is vital. DWs continue to be relevant, since as they support operationalized analytics, and enable business value from machine data and other new forms of big data. This TDWI Best Practices report covers how to modernize a DW environment, to keep it competitive and aligned with business goals, in the new age of big data analytics. This report covers: • The many options – both old and new – for modernizing a data warehouse • New technologies, products, and practices to real-world use cases • How to extend the lifespan, range of uses, and value of existing data warehouses
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pentaho, data warehouse, modernization, big data, bug data analytics, best practices, networking, it management, wireless, platforms, data management, business technology
    
Pentaho
Published By: Pentaho     Published Date: Apr 28, 2016
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
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pentaho, best practices, hadoop, next generation analytics, platforms, infrastructure, data, analytics in organizations, it management, wireless, enterprise applications, data management, business technology, data center
    
Pentaho
Published By: IBM     Published Date: Aug 31, 2012
As those hosting transactional data on System z today already realize, it is one of the most secure, highly available and reliable platforms on the market - now see how organizations are bringing their analytics to IBM System z to better harness their data and gain greater business insights while containing cost and reducing complexity.
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IBM
Published By: Teradata     Published Date: Feb 26, 2013
This survey and research report discusses shifts in the data management landscape and the movement to align data with operational and analytical workloads creating the best possible unified data architecture platform. Read on to learn more.
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big data, survey report, data management, landscape, movement, align data, operational and analytics workloads, business intelligence, terdata, business technology, data center
    
Teradata
Published By: Birst     Published Date: Jul 16, 2013
Discover seven indications that you need advanced analytics for your CRM application and why they matter. Learn about common CRM data analysis pain points and how advanced CRM analytics can solve them.
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business intelligence, agile bi, self service bi, bi in the cloud, unified bi, mobile bi, embedded analytics, business analytics, sales analytics, hr analytics, marketing analytics, financial analytics, supply chain analytics, automated data management, dashboards, infrastructure
    
Birst
Published By: Adobe     Published Date: May 15, 2018
Adobe is the only Leader in Digital Intelligence Platforms. Digital intelligence with scope and depth. Your customers come to you from different places, so your data insights should do the same thing. Adobe Experience Cloud’s digital marking and analytics solutions help you combine insights from existing, new, and emerging channels. Read the Forrester Wave™: Digital Intelligence Platforms, Q2 2017 to find out why we stand alone among DI platform vendors.
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Adobe
Published By: Sailthru     Published Date: Aug 15, 2016
Download this guide to discover how to find a partner that moves beyond antiquated batch-and-blast methodologies to impact: -Customer retention rates and revenue -Personalization sophistication -Cross-channel marketing capabilities -Effective reporting, impactful data and predictive analytics Who should download: -Internet Retailer Top 1,000 Digital Marketing executives -Directors of CRM and Ecomme
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sailthru, retail, rfp, request for proposal, marketing, internet retailer, top 1000
    
Sailthru
Published By: BlueData     Published Date: Aug 19, 2015
Big Data is on virtually every enterprise’s to-do list these days. Recognizing both its potential and competitive advantage, companies are aligning a vast array of resources to access and analyze this strategic asset. However, despite best intentions, the majority of these Big Data initiatives are either extremely slow in their implementation or are not yielding the results and benefits that enterprises expect. Download this white paper to learn how to solve the Big Data intention-deployment gap and see how you can make your infrastructure in a flexible, easy-to-use platform that will provide in-depth analytics.
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big data, big data intention-deployment, in-depth analytics, hadoop, data management, data center
    
BlueData
Published By: Workterra     Published Date: Nov 10, 2017
Mid-market HR today is being asked to be a business partner in areas that range from compliance to employee engagement. They need to be able to connect the dots among various sources of employee data to deliver better-informed business decisions to help achieve strategic goals. Connecting those dots and delivering those results demands more HR firepower and greater data visibility than the manual or homegrown processes and systems often used by mid-market organizations can deliver. On the other hand, most mid-market companies aren’t ready for the intricacies or expense of human capital management (HCM) systems designed for enterprise-level organizations. The answer for forward-thinking HR leaders who want to boost their team’s capabilities and play a greater role in their company’s future is having core HR functionality designed into an integrated benefits administration solution. Automated HR that delivers core HR features as part of its architecture — not as an afterthought or a separate, stand-alone module — gives HR leaders: • The tools they need to better handle their administrative work • The data and analytics necessary to better coordinate programs and more confidently make strategic decisions • A user experience that makes life easier for HR and employees
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Workterra
Published By: Landis + Gyr     Published Date: Mar 17, 2016
The rapid acceleration of Distributed Energy Resources (DER) presents a range of challenges for electric utility management. The good news is that a strategic approach, one that taps the power of data analytics, can meet the rising need to manage DER. Download this white paper, to learn about the current state of DER and how to get started with a smart grid analytics solution: • Cost-benefit analysis • Challenges of integrated DERs • Planning considerations • Advanced analytics tools and predictive grid analytics benefits • Choosing a platform
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cost-benefit analysis, der, analytics, platform, utility, smart grid
    
Landis + Gyr
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