data and analytics

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Published By: SAP     Published Date: Jul 18, 2016
As your business transitions to a digital enterprise, you can start to give your employees, partners, and customers immediate, data-driven, and even predictive insight into what’s going on – in a way that’s relevant for them. Strategic use of on premise and cloud-based analytics accelerates this process. Read the solution brief to see how SAP is continuing to invest in on premise solutions as part of their effort to reimagine analytics.
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SAP
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 21, 2016
Between the Internet of Things, customer experience and loyalty programs, social network monitoring, connected enterprise systems and other information sources, today's organizations have access to more data than they ever had before-and frankly, more than they may know what to do with. The challenge is to not just understand that data, but actualize it and use it to recognize real business value. This ebook will walk you through a sample scenario with Albert, a data scientist who wants to put text analytics to work by using the Word2vec algorithm and other data science tools.
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ibm, analytics, aps, aps data, open data science, data science, word2vec, enterprise applications, business technology, data center
    
IBM
Published By: Oracle     Published Date: Oct 20, 2017
What do these market-defining trends have in common? · Analytics for all · Analytics as competitive differentiator · Internet of Things · Artificial intelligence/Machine learning/Cognitive computing · Real-time analytics/event management They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise? It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital is also a
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Oracle
Published By: IBM     Published Date: Jan 19, 2017
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, analytics, ecm, data, big data, information governance, enterprise applications, data management, business technology
    
IBM
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: Jan 30, 2017
Analytics has permeated, virtually, every department within an organization. It’s no longer a ‘nice to have’. It’s an organizational imperative. HR, specifically, collects a wealth of data; from recruiting applications, employee surveys, performance management data and it sits in systems that remain largely untapped. This data can help drive strategic decisions about your workforce. Analytic tools have, historically, been difficult to use and required heavy IT lifting in order to get the most out of them. What if an analytics system learned and continue to learn as it experienced new information, new scenarios, and new responses. This is referred to as Cognitive Computing and is key to providing an analytics system that is easy to use but extremely powerful.
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ibm, talent analytics, cognitive computing, analytics, engagement
    
IBM
Published By: IBM     Published Date: Aug 24, 2017
Data governance is all about managing data, by revising that data to standardize it and bring consistency to the way it is used across numerous business initiatives. What’s more, data governance ensures that critical data is available at the right time to the right person, in a standardized and reliable form. A benefit that fuels better organization of business operations, resulting in improved productivity and efficiency of that organization. Thus, the importance of proper data governance cannot be understated. The concepts of data governance have evolved, where the first iteration of data governance, often referred to as version 1.0, focused on three simplistic elements: objectives, structure and processes; having a limited focus and scope due to its tactical usage. The opportunity from the growing value of data in the realm of analytics, business intelligence, and generating insights was left unrealized. Today, organizations are moving towards what can be called Data Governance 2.0,
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ibm, unified governance strategy, data management, data governance
    
IBM
Published By: IBM     Published Date: Oct 17, 2017
The data quality tools market continues to show strong revenue growth, driven by cost, process optimization and digital business initiatives. Applying data quality tools to existing and emerging business scenarios will enable data and analytics leaders to deliver greater business value.
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IBM
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: Alteryx, Inc.     Published Date: Apr 21, 2017
As a financial services provider, you have probably invested hundreds of thousands, if not millions of dollars, in building an analytic infrastructure. But, do your line-of-business analysts and managers have access to the data and insights they need, when they need them? Three ways Alteryx can help you improve customer experience, manage risk and increase operational efficiency Case studies on how your peer financial services companies are using self-service data analytics for a competitive edge
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Alteryx, Inc.
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
The traditional multiple-step, multi-tool legacy approach is a slow, time-consuming, and in most cases, a costly process that prevents organizations from making faster decisions with confidence. Data analysts today need an agile solution that empowers them to take charge of the entire analytics process. Download The Definitive Guide to Self-Service Data Analytics to: Understand why traditional analytic tools designed for data scientists are not ideal for data analysts like you Learn how self-service data analytics delivers the ease of use, speed, flexibility, and scalability you require See how Alteryx stacks up against traditional data prep and analytics tools
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Alteryx, Inc.
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
Data Analytics has become critical for many business decision makers. However, many of these managers and data analysts still rely on spreadsheets and other legacy-era tools that fall far short of current needs. As a result, they also rely heavily on a virtual army of data specialists and scientists, working under the auspices of a centralized analytics group, to prepare, blend, analyze, and even report on the critical data they need for decision making. Download this new paper to get the details behind self-service data analytics, and how it lets business analysts: Take charge of the entire analytical process, instead of relying on other departments Overcome limitations of legacy tools to save time and prevent errors Make more comprehensive and insightful business decisions at speed
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Alteryx, Inc.
Published By: Privacera     Published Date: Oct 23, 2017
Trends indicate that every company should embrace big data and analytics – there’s clearly incredible opportunity for enterprises to derive value from data. But not all companies are clamoring to jump on board with building teams and defining initiatives. The reality is enterprises are analyzing only 0.5% of their data, according to recent study by MIT Technology Review. What’s holding these companies back? This paper will cover the categories of risk and some of the constraints at play, as well as five recommendations to managing and mitigating that risk.
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Privacera
Published By: IBM     Published Date: Jun 04, 2018
"The appearance of your reports and dashboards – the actual visual appearance of your data analysis -- is important. An ugly or confusing report may be dismissed, even though it contains valuable insights about your data. Cognos Analytics has a long track record of high quality analytic insight, and now, we added a lot of new capabilities designed to help even novice users quickly and easily produce great-looking and consumable reports you can trust. Watch this webinar to learn: • How you can more effectively communicate with data. • What constitutes an intuitive and highly navigable report • How take advantage of some of the new capabilities in Cognos Analytics to create reports that are more compelling and understandable in less time. • Some of the new and exciting capabilities coming to Cognos Analytics in 2018 (hint: more intelligent capabilities with enhancements to Natural Language Processing, data discovery and Machine Learning)."
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data analysis, data analytics, dashboards
    
IBM
Published By: IBM     Published Date: Jun 04, 2018
"Today’s business users want to use all types of data to create compelling, shareable visualizations. But charts and graphs alone may not convey all the information, especially when they are part of a complex series. An audience can best understand analytic results when those results tell a story that connects all the pieces together. The right visuals can also reinforce the lessons buried in the data. Stories are powerful mechanism to communicate with people. Stories stick and make insights actionable, so it goes without saying that storytelling is a very powerful (soft) skill. In this webinar, you'll learn how to effectively apply storytelling best practices to get your message across. Especially in the world of BI, it is getting more and more important to effectively communicate business results. Watch this webinar to learn how to use IBM Cognos Analytics to: · Create the important elements of a good story · Put the data in context · Select the best type of ch
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data analytics, data storytelling, business intelligence
    
IBM
Published By: IBM     Published Date: Jun 04, 2018
"What would you do if you didn’t have to rely on disparate analytics solutions to meet the needs of business users while following the rules of IT? View this 'Charting Your Analytical Future' webinar to learn about a world of innovation and independence for users that does not limit the confidence and controls of IT. With the cognitive-guided self-service features available in IBM business analytics solutions, more users than ever before can get the answers they need. Next-generation business analytics capabilities make it possible to access relevant data, prepare it for analysis and understand performance. But it doesn’t stop there. Users can package the results in a visually-appealing format and share them throughout the organization. Don’t miss this opportunity to hear how you can: * Benefit from advanced analytics without the complexity * Operationalize insights and dashboards from a collection of trusted data sources * Tell your story with rich visualizations and geospati
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business analytics, analytics solutions
    
IBM
Published By: IBM     Published Date: Jul 02, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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IBM
Published By: IBM     Published Date: Jul 05, 2018
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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IBM
Published By: Group M_IBM Q418     Published Date: Dec 18, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does.
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Group M_IBM Q418
Published By: ServiceNow     Published Date: Sep 18, 2018
What is a performance based business? A performance-based business is an organization guided by data-driven decisions. It is proactive, self-aware, and highly competitive. Data isn’t siloed in a business analytics department. Instead, the right people have the right data at the right time and in the right context. The top 5 reasons to become a performance-based business: 1. Get better results. 2. Align your entire business. 3. Make data-driven decisions. 4. Manage change more effectively. 5. Spot trends faster. Discover how ServiceNow Performance Analytics could benefit your business by downloading this eBook.
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performance, business, data, servicenow
    
ServiceNow
Published By: ServiceNow     Published Date: Sep 18, 2018
Worldpay deployed ServiceNow Performance Analytics to replace multiple data tools and promote the use of analytics throughout its organization for improved decision making. Nucleus found the project enabled the company to boost analyst productivity, while simultaneously increasing data accessibility and engagement for hundreds of additional employees. Download this case study to learn more
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nucleus, research, worldpay, servicenow
    
ServiceNow
Published By: TIBCO Software APAC     Published Date: Feb 14, 2019
Analyst firms Gartner, Inc. and Forrester are projecting accelerated data virtualization adoption for both first-time and expanded deployments. What are the uses cases for this technology? At its Data and Analytics Summit in London in March 2018, Gartner answered this question by identifying 13 data virtualization use cases. This paper explores each of these use cases by: Identifying key requirements Showing how you can apply TIBCO® Data Virtualization to address these needs Listing the benefits you can expect when implementing TIBCO Data Virtualization for the use case
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TIBCO Software APAC
Published By: TIBCO Software APAC     Published Date: Feb 14, 2019
Digital business initiatives have expanded in scope and complexity as companies have increased the rate of digital innovation to capture new market opportunities. As applications built using fine-grained microservices and functions become pervasive, many companies are seeing the need to go beyond traditional API management to execute new architectural patterns and use cases. APIs are evolving both in the way they are structured and in how they are used, to not only securely expose data to partners, but to create ecosystems of internal and/or third-party developers. In this datasheet, learn how you can use TIBCO Cloud™ Mashery® to: Create an internal and external developer ecosystem Secure your data and scale distribution Optimize and manage microservices Expand your partner network Run analytics on your API performance
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TIBCO Software APAC
Published By: TIBCO Software APAC     Published Date: Feb 14, 2019
Tips and best practices for data analytics executives Organizations today understand the value to be derived from arguably their greatest asset—data. When successfully aggregated and analyzed, data can unlock valuable insights, solve problems, improve products and services, and help companies gain a competitive edge. However, analytics executives face significant challenges in collecting, validating and analyzing data to deliver the right analytic insight to the right person at the right time. This e-book is designed to help. First, we'll explore the growing expectations for data analytics and the rise of the analytics executive. Then we'll explore a range of specific challenges those executives face, including those around data blending, analytics, and the organization itself, and offer best practices and strategies for meeting them. We'll also provide a short overview of TIBCO Statistica, an easy-to-use predictive analytics software solution designed to turn big data into your bigg
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TIBCO Software APAC
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