business analytics

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Published By: Oracle     Published Date: Nov 05, 2013
As social media use has grown, an urgent need has emerged to correlate the information generated through social data with existing consumer information, and integrate it with sophisticated data management systems. This white paper describes how organizations can blend social insights with more-traditional data in an integrated customer data hub to optimize social strategies and create outreach efforts, new products, and campaigns grounded in real-time, repeatable, automated, and scalable analysis.
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business intelligence, integrated marketing, social media strategy, content marketing, insight, social data, customer hub, social analytics
    
Oracle
Published By: Oracle     Published Date: Nov 14, 2016
Démo Data Visualization dans le domaine de la vente par Sylvain Fortier, Business Intelligence & Big Data Analytics Principal Sales Consultant d'Oracle France durant la matinée Oracle Cloud Café autour du thème de la Data Visualization et Analytics.
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Oracle
Published By: Oracle     Published Date: Nov 14, 2016
Démo Data Visualization dans le domaine de la vente par Sylvain Fortier, Business Intelligence & Big Data Analytics Principal Sales Consultant d'Oracle France durant la matinée Oracle Cloud Café autour du thème de la Data Visualization et Analytics.
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Oracle
Published By: IBM     Published Date: Jan 09, 2014
Today, large organizations are being buffeted by a host of changes, many of them unexpected or unfamiliar. Business information is virtually exploding in size, kind and locale, taxing the abilities of even the most progressive enterprises to keep up. Mobile technologies and business analytics that were once exclusively used by employees with specialized needs and skills are now common across the entire workforce. As a result of all this, IT is bending under the strain of developing and delivering necessary new services while at the same time maintaining core service quality. This report will consider these issues, as well as IBM’s position in and efforts around developing next generation enterprise systems solutions, including its System z mainframes, POWER7+ processor-based Power Systems servers and System Storage offerings focused on those areas and use cases.
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enterprise systems, system performance, power7+, power systems servers, system storage, it infrastructure, analytics solutions, business analytics
    
IBM
Published By: Cisco     Published Date: Sep 15, 2015
IDC finds that leveraging data analytics in business decisions is becoming a top priority for an increasing number of companies. This in turn is placing new demands on IT organizations; the need is twofold: to manage new streams of unstructured data from sources such as social media and to speed response times to deliver real-time analytics.
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sap, analytics, data, real-time
    
Cisco
Published By: NetApp     Published Date: Mar 05, 2018
Did you know that by 2020, 50% of analytic queries will be generated using search, natural-language processing or voice, or will be automatically generated? Read the Gartner report Technology Insight for Modern Analytics and Business Intelligence Platforms and find out how to meet the time-to-insight demands of today's competitive business environment. Learn how to: • Determine when to use existing, traditional BI technologies versus modern analytics and BI • Broaden data access beyond relational systems • Adopt new approaches to data modeling
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netapp, database performance, flash storage, data management, cost challenges
    
NetApp
Published By: NetApp     Published Date: Mar 05, 2018
The proliferation of business unit cloud use is primarily motivated by digital transformation's need for innovation and agility in big data and real-time analytics, rather than cost optimization, which causes overspending. CIOs should use three moves to gain business influence and optimize costs.
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netapp, database performance, flash storage, data management, cost challenges
    
NetApp
Published By: IBM     Published Date: May 19, 2015
Traditionally, business intelligence (BI) has looked backward at what has happened. In today’s marketplace, enterprises need to look ahead. From predictive to prescriptive intelligence, TDWI and IBM look at what businesses need most.
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business intelligence, prescriptive intelligence, predictive analytics, immersive user experience, analytic technology, informative visualization, virtualization, cloud computing
    
IBM
Published By: IBM     Published Date: May 20, 2015
An analytics-based marketing platform can help marketers tackle the opportunities and challenges of a data and consumer-driven marketplace.
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IBM
Published By: IBM     Published Date: May 22, 2015
In this webinar, we will discuss the broad range of IBM deployment approaches that can help organizations solve their business challenges and achieve a higher ROI from analytics.
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analytics, roi, management, ibm, strategy, bandwidth management
    
IBM
Published By: FICO     Published Date: Sep 02, 2016
The unifying concept that defines FICO and its substantial technology and solutions stack is Decision Management. This term has not yet become mainstream - but it will. All business analytics activities are performed with the single aim of improving the accuracy and efficiency of business decisions. This applies to business intelligence, data visualization, data mining, business rules management, and many other forms of analysis. Unifying these activities under a single discipline means that currently fragmented analytical efforts can be combined into a single whole, with benefits that will be discussed in this review.
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FICO
Published By: FICO     Published Date: Dec 04, 2017
As consumers, we’re all having more experiences that seem almost magical: You’re in a mall when suddenly your smartphone beeps. It’s an offer for 20% off a pair of shoes you’ve been looking at online — from the store you just walked past! As business people, we know it’s not magic, but rather analytics powering these outstanding customer experiences. Analytics have evolved to the point where they answer an expanding range of useful questions. But understanding the different types of analytics – descriptive, diagnostic, predictive and prescriptive - and how to use them in your business can be challenging. Download the eBook to learn about the least understood – yet most powerful – tool in the analytic arsenal. Prescriptive analytics enable you to estimate and compare the likely outcomes of any number of actions, and choose the very best action to advance business objectives. Getting there isn’t as difficult as you think. Start your journey. Download the eBook today.
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profits, analytics, credit, social, media, services, customer, consumers
    
FICO
Published By: Pega     Published Date: Jun 21, 2016
IT leaders working on customer service projects must display an incredible amount of diligence. An organization’s CRM system has become its lifeline to customers, but as customer needs evolve so has the requirements of CRM. According to Gartner, today’s CRM solution must include a laundry list of capabilities outside its traditional core functionality including: native mobile support of the vendor's customer service and support business applications; real-time analytics; industry-specific functionality and workflow; context mining of voice and text; scalable cloud-based systems; social media engagement; suggested next agent action; multimodal capabilities, such as chat within mobile self-service; and even co-browsing. Gartner surveyed the CRM field and evaluated each vendor including Pegasystems.
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Pega
Published By: Qlik     Published Date: Oct 13, 2015
Business intelligence and analytics leaders must re-evaluate and evolve the capabilities of their teams to ensure that they can leverage bimodal work practices to engage, communicate and adapt to new developments in business analytics, including diagnostic and predictive analytics.
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qlik, data discovery, business intelligence, analytics, user produced content, cloud, social, data visualization
    
Qlik
Published By: Qlik     Published Date: Oct 13, 2015
Data discovery appeals strongly to business users, but some business intelligence leaders are reluctant to ensure adoption. Data discovery is filling the gap between traditional BI and advanced analytics, and this research explains why and how BI leaders should support its use.
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qlik, data discovery, business intelligence, analytics, user produced content
    
Qlik
Published By: IBM     Published Date: Mar 31, 2016
"The market buzz around APIs has distorted executive's thought processes about how to make money from APIs. Our guest speaker, Forrester analyst Randy Heffner, will tell the real truth about how to drive value from APIs. Who Should Read/View This webcast: business audience Attend to also learn how to: Provide business users with real-time information for more informed decision making Leverage the latest cloud, mobile, and analytics enhancements in IIB v10 Use the IIB Healthcare Pack to accelerate development and deployment of integration solutions Who Should Attend this Webcast: business audience"
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ibm, api, integration, application program interface, middleware
    
IBM
Published By: IBM     Published Date: Apr 15, 2016
This white paper takes a look at the current challenges that many organizations face in addressing this growing need. It examines the different types of users and stakeholders who need or want more self-service, and lays out four factors that are critical to realizing the full potential of self-service analytics.
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ibm, business analytics, self-service analytics, business intelligence
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
By modeling, analyzing, and improving their existing processes, Colorado-based, Elevations Credit Union has been able to drive out inefficiencies and increase their revenues by delighting their customers. IBM Blueworks Live is the tool that’s been at the heart of Elevations gaining visibility and insight into their existing processes, and helping them drive cross-enterprise engagement and viral cultural change. .
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ibm, process improvement, business results, elevations credit union, ibm blueworks live, analytics, application services, networking
    
IBM
Published By: IBM     Published Date: Jul 12, 2016
As most companies now realize, analytics is increasingly more of an integral part of their day-to-day business operations. In a recent survey by a global research firm, 80% of CIOs stated that transition from backward-looking, passive analysis must shift to forward-looking predictive analytics. The challenge is that many analytic solutions are aligned to a specific platform, tied to inflexible programming models and requiring vast data movement. In this webcast, Forrester and experts from IBM will highlight how technology like Apache Spark on z/OS allows businesses to extract deep customer insight without the cost, latency and security risks of data movement throughout the enterprise.
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ibm, forrester, apache spark, spark technology, z systems, security
    
IBM
Published By: IBM     Published Date: Jul 20, 2016
A successful business case is one that enables your organisation’s business leaders to make the right decisionabout a Talent Analytics investment. In this report we highlight the key aspects you need to think about as you create your own business case for Talent Analytics, starting with getting a clear handle on why it is a worthwhile investment for your organisation, but also addressing considerations such as budget and resourcing concerns, how you can measure the success of your initiative and demonstrate ROI, and the major risks you need to bear in mind over the lifetime of the initiative.
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ibm, mwd advisors, talent analytics
    
IBM
Published By: IBM     Published Date: Jul 21, 2016
View this video to learn: - How to "push the needle" for your business by streamlining your census survey - How and why to implement pulse surveys - Why analytics can be a game changer for your organization
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ibm, smarter workforce, employee engagement, employee voice, business results, census survey, pulse survey
    
IBM
Published By: IBM     Published Date: Dec 05, 2016
Learn directly from KONE's expert about their recent IoT experience in implementing predictive maintenance (PMQ) and IoT. The session will cover: 1) KONE's business area that the PMQ and IoT solution is supporting, and the metrics used to measure success; 2) KONE's Predictive Maintenance and IoT Platform use case, key personas, savings and benefits realized; and 3) Observations from implementation, including: a) The analytics journey at KONE; b) Organizational change (culture, processes, etc.); c) Measurable maintenance benefits; d) Implementation considerations, learnings, going forward; and e) Future projects and capabilities.
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ibm, leadership, watson, watson iot, predictive maintenance
    
IBM
Published By: AWS     Published Date: May 18, 2018
We’ve become a world of instant information. We carry mobile devices that answer questions in seconds and we track our morning runs from screens on our wrists. News spreads immediately across our social feeds, and traffic alerts direct us away from road closures. As consumers, we have come to expect answers now, in real time. Until recently, businesses that were seeking information about their customers, products, or applications, in real time, were challenged to do so. Streaming data, such as website clickstreams, application logs, and IoT device telemetry, could be ingested but not analyzed in real time for any kind of immediate action. For years, analytics were understood to be a snapshot of the past, but never a window into the present. Reports could show us yesterday’s sales figures, but not what customers are buying right now. Then, along came the cloud. With the emergence of cloud computing, and new technologies leveraging its inherent scalability and agility, streaming data
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AWS
Published By: AWS     Published Date: Sep 04, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics.
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AWS
Published By: AWS     Published Date: Sep 04, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technology
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AWS
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