analytical

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Published By: Oco, Inc.     Published Date: Jun 24, 2008
As a Services Executive are you struggling with questions regarding what to measure, how to effectively engage with your customers, and what information should be leveraged and shared with service-chain partners and customers? Leading edge organizations are making tools and data available to their suppliers and customers with aggregated information from multiple data systems. Service-chain partners and customer personnel can now see the same views of service performance and activity. This is the next frontier to creating customer "stickiness" and business growth.
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business analytics, oco, service management, analytical applications, dashboard, analytic, growth
    
Oco, Inc.
Published By: Oco, Inc.     Published Date: Nov 12, 2008
Many companies have business intelligence (BI) tools and infrastructure that serve their business’ needs; however, certain functional departments, business units, or key business initiatives often don’t yet have the BI tools that they need in place.  There is a new approach to BI to address those pressing business needs that leverages the existing BI infrastructure and can deliver value to the business in weeks rather than months and at a fraction of the cost of a traditional BI solution. Learn how Complementary BI leverages Software-as-a-Service (SaaS) BI solutions to address targeted business needs in a way that complements in-house BI systems, leading to a win-win situation for business users and IT analytical tools to business users.
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oco, business intelligence, software-as-a-service, roi
    
Oco, Inc.
Published By: Oracle     Published Date: Nov 27, 2013
Fact: In the next three years, 53% of CFOs estimate that over half of their enterprise transactions will be delivered through the cloud, up from the 12 percent who use that delivery mechanism today. In addition to non-core business processes like project management and email, strategic CFOs are also starting to embrace the cloud to deliver core ERP processes, including financial management, human capital management, and procurement. Rather than view the cloud just as a cost-saving platform, they recognize the strategic benefits that the cloud delivers to get critical growth initiatives up and running quickly, whether that’s using the cloud to quickly upgrade to a new application, or delivering new mobile or analytical capabilities to employees.
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cloud crm, technology, business needs, best practices, crm solution, solution at scale, sales, marketing, customer relationship management, pipeline
    
Oracle
Published By: Lumension     Published Date: Jun 05, 2015
Microsoft's System Center Configuration Manager doesn't handle every aspect of Linux/UNIX and third-party application security. Here's how to augment and leverage SCCM to close the gaps.
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it security, data center, patch, software, application, analytical applications, database development, database security, employee performance, productivity
    
Lumension
Published By: IBM     Published Date: Aug 20, 2015
This report provides practical guidance on the critical 10 steps for the first 100 days of setting up an analytically enabled HR function.
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workforce analytics, data analytics, hr function, talent management, recruitment, best practices, ibm smarter workforce, talent analytics
    
IBM
Published By: SnowFlake     Published Date: Jul 08, 2016
This EMA case study profiles the implementation of the Snowflake Elastic Data Warehouse, a new generation of cloud-based data warehouses, by Accordant Media. This document details significant tangible and intangible improvements and opportunities the Snowflake solution created for the Accordant Media infrastructure and analytical teams.
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snowflake, media, data, technology, cloud-based data, best practices
    
SnowFlake
Published By: SAP     Published Date: May 14, 2008
As information flows more freely in the business world, decisions need to be made quicker and based on sturdier data. The analytical capability that was once reserved for large enterprises has now permeated the world of Small to Medium Businesses (SMBs) and provided a solid foundation of visibility into what really matters to these companies.
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business intelligence, sap
    
SAP
Published By: SAP     Published Date: Jun 22, 2009
Find out how to meet the challenges facing your midsize company and benefit from the road map that takes you through the process of deploying a BI solution, enabling you to start small and then build incrementally on your initial success to make fact-based and BI-driven decision making pervasive in your company.
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sap, midsize, business intelligence, economy, soa, infrastructure, tco, total cost of ownership, kpi, key performance indicators, tco, total cost of ownership, sap application, sap netweaver bw, online analytical processing, olap
    
SAP
Published By: SAP     Published Date: Mar 24, 2011
In spite of the growth of virtual business activities performed via the World Wide Web, every business transaction or operation is performed at a physical place. And as handheld GPS devices drive a growing awareness of the concept of "location," people are increasingly looking for operational efficiencies, revenue growth, or more effective management as a result of geographic data services and location-based intelligence. In this white paper, David Loshin, president of Knowledge Integrity, Inc., introduces geographic data services (such as geocoding and proximity matching) and discusses how they are employed in both operational and analytical business applications. The paper also reviews analytical techniques applied across many types of organizations and examines a number of industry-specific usage scenarios.
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location-based bi, business value, geographic enhancement
    
SAP
Published By: IBM     Published Date: Apr 15, 2016
This report examines the current state of self-service analytics across all industries and company sizes. It also highlights the technology decisions and analytical performance of organizations that reported high levels of self-service in their analytical use base.
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ibm, analytics, self-service analytics, business analytics, analytical performance
    
IBM
Published By: BlackBerry Cylance     Published Date: Jul 02, 2018
The 21st century marks the rise of artificial intelligence (AI) and machine learning capabilities for mass consumption. A staggering surge of machine learning has been applied for myriad of uses — from self-driving cars to curing cancer. AI and machine learning have only recently entered the world of cybersecurity, but it’s occurring just in time. According to Gartner Research, the total market for all security will surpass $100B in 2019. Companies are looking to spend on innovation to secure against cyberthreats. As a result, more tech startups today tout AI to secure funding; and more established vendors now claim to embed machine learning in their products. Yet, the hype around AI and machine learning — what they are and how they work — has created confusion in the marketplace. How do you make sense of the claims? Can you test for yourself to know the truth? Cylance leads the cybersecurity world of AI. The company spearheaded an innovation revolution by replacing legacy antivirus software with predictive, preventative solutions and services that protect the endpoint — and the organization. Cylance stops zero-day threats and the most sophisticated known and unknown attacks. Read more in this analytical white paper.
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cylance, endpoint, protection, cyber, security
    
BlackBerry Cylance
Published By: SAS     Published Date: Mar 06, 2018
Information on artificial intelligence (AI) is flooding the market, media and social channels. Without doubt, it’s certainly a topic worth the attention. But, it can be difficult to sift through market hype and grandiose promises to understand exactly how AI can be applied in practical and reliable solutions. Like most technological advances, incorporating new technology into business processes requires significant leadership and effective direction that all stakeholders can easily understand.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated drive as you read the morning news. We are getting very close to that kind of scenario, and companies like Ford expect to have production vehicles in the latter part of 2020. Driverless cars are just one popular example of machine learning. It’s also used in countless applications such as predicting fraud, identifying terrorists, recommending the right products to customers at the right time, and correctly identifying medical symptoms to prescribe appropriate treatments. The concept of machine learning has been around for decades. What’s new is that it can now be applied to huge quantities of data. Cheaper data storage, distributed processing, more powerful computers and new analytical opportunities have dramatically increased interest in machine learning systems. Other reasons for the increased momentum include: maturing capabilities with methods and algorithms refactored to run in memory; the
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SAS
Published By: SAS     Published Date: Mar 06, 2018
Business intelligence has come a long way ? from assistance with report generation to self-service platforms for discovery and analytical insight. As technological capabilities and business aptitude with information continue to advance, the next generation of BI will be even more capable and valuable to the enterprise. To discuss today’s success factors and tomorrow’s opportunities, IIA spoke with Rick Styll, Senior Manager, Visual Analytics Product Management at SAS, and Tapan Patel, Principal Product Marketing Manager at SAS.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
Better health care at lower costs, for everyone – how do health care providers get there? Understanding the gaps in patient care, patient needs, and the geographic distribution of the patient population are important elements to consider when making decisions about improving the quality of care and reducing its costs. To effectively analyze gaps in patient care, the data needs to be in a single place or system. However, in many organizations, data is spread across a myriad of spreadsheets and database systems. Data not organized for visual exploration and coherent analysis isn’t useful for decision making. Hence the need for visually appealing and scalable analytical tools to help organizations be more efficient, effective and economically successful.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
Enhanced regulatory pressure requires continuous evaluation of your bank’s risks. To meet these demands, the AML industry has turned to analytical/statistical methodologies to: • Improve monitoring programs. • Reduce false-positive alerts. • Increase monitoring coverage. • Reduce the rapidly escalating financial cost of maintaining AML programs.
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SAS
Published By: SPSS Inc.     Published Date: Mar 31, 2009
In an intensely competitive marketplace, knowledge is power. The more an airline can learn about what its customers like and don't like about its offerings, the more effective it can be at building customer loyalty and maximizing its revenues.
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spss, american airlines, customer loyalty, maximize revenues, roi, specialized market intelligence, production of information, increased productivity, best practices, statistical analysis, analytical methods, statistics, crm, consumer research, data trends, program macros, research, data management, decision-making
    
SPSS Inc.
Published By: ClickSquared     Published Date: Jul 07, 2009
Learn how by achieving a 360-degree view of customer interests, markets can achieve unprecedented levels of: *Personalization, *Timing, *Relevance, *Cost-efficiency, *Accountability
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clicksquared, interactive relationship marketing, lifecycle, irm, web 2.0, granular personalization, analytical marketing models, database marketing, personalization, timing, relevance, click squared, choreograph online, real-time, offline, episodic, cost dynamics, rapid deployment, domain expertise, personalization
    
ClickSquared
Published By: SAS     Published Date: Aug 27, 2010
Forget spreadsheets. Organizations that are winning in this down economy are using automated analytical tools to take a more scientific approach to decision making through observation, experimentation and measurement to improve their business processes.
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sas, analytics software, business intelligence, data mining, automated analytical tools, computerworld
    
SAS
Published By: SAS     Published Date: Jan 31, 2011
Companies are becoming more analytically mature and are developing greater analytical capabilities. Many companies are also creating a context for analytics, with analytical cultures and processes. When companies compete based on analytics, analytics is having a positive bottom-line impact.
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sas, prescriptive analytics, harvard business
    
SAS
Published By: SAS     Published Date: Mar 01, 2012
This Aberdeen Research Brief draws on three discrete data sets in order to understand the tangible business impact of effective analytics in the SMB market.
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SAS
Published By: SAS     Published Date: Mar 01, 2012
Michael Lock of the Aberdeen Group focuses on the effect of end user adoption, pervasiveness, and engagement of business intelligence on business performance. Learn the necessary steps to establishing self-service business analytics.
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SAS
Published By: SAS     Published Date: Mar 14, 2014
This Q&A with Tom Davenport, Director of Research for the International Institute for Analytics (IIA), will help you understand how analytics is evolving, where you need to go, and how to get there.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, analytics, analytical study, visualization deployment, deployment, institute for analytics
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
Stop to think about how - and how often - your business interacts with customers. Most organizations believe that only a small fraction of data on interactions generated are effectively put to use. Why is that? Check out this whitepaper to see.
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sas, voc, voice of customer, visual text analytics, best practices, customer voice, sound of sentiment, text data, customer data, analytical processing, structured data, enriched dataset, reporting, automatic generation, text analytics, text mining, data exploration
    
SAS
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