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Published By: SAS     Published Date: Mar 06, 2018
The Connected Customer is an individual who is intimately connected to the data, outcomes, decisions, and staff associated with any relationship to an organization. This intensely personal connection is not just a matter of the most recent transaction, but represents a combination of connected data, connected analytics, and collaborative decisions associated with improving the customer’s relationship with the organization over time. In this report, Blue Hill explores the key traits associated with supporting the Connected Customer through the Internet of Things, and provides guidance on why the Internet of Things will be essential across the general business landscape
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Published By: SAS     Published Date: Mar 06, 2018
The most recent decade has seen rapid advances in connectivity, mobility, analytics, scalability, and data, spawning what has been called the fourth industrial revolution, or Industry 4.0. This fourth industrial revolution has digitalized operations and resulted in transformations in manufacturing efficiency, supply chain performance, product innovation, and in some cases enabled entirely new business models. This transformation should be top of mind for quality leaders, as quality improvement and monitoring are among the top use cases for Industry 4.0. Quality 4.0 is closely aligning quality management with Industry 4.0 to enable enterprise efficiencies, performance, innovation and business models. However, much of the market isn’t focusing on Quality 4.0, since many quality teams are still trying to solve yesterday’s problems: inefficiency caused by fragmented systems, manual metrics calculations, quality teams independently performing quality work with minimal cross-functional own
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Published By: SAS     Published Date: Mar 06, 2018
The Internet of Things enables retailers to do three basics better and faster: 1) Sensing who customers are and what they’re doing, 2) Understanding customer behavior and preferences, and 3)Acting on that insight to create a more engaging customer experience. - There are high-potential IoT applications in supply chain, in “smart store” operations, and especially in providing an engaging experience to the “connected customer.” IoT data can anticipate where the customer is headed and how to meet her there. - Much of the IoT ground, in both data management and analytics, may be unfamiliar. Retailers and their IT organizations have to be realistic about the technological challenges, their own capabilities, and where they need assistance. - To differentiate through IoT, focus on the analytics. Devices and their data — and even their platforms — are commodities. Advantage goes to the retailer who does the most with the data to engage the connected customer.
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Published By: SAS     Published Date: Apr 04, 2018
Location analytics is the process of integrating geographical data into business intelligence (BI) and analytics-led decision making. Location analytics creates meaningful insight from relationships found in geospatial data to solve a broad variety of business and social problems. Location data is found everywhere – with an item or a device, in a conversation or behavior, in machines or sensors, tied to a customer or competitor, attached to a database record or recorded from vehicles or other moving objects. Organizations want to take advantage of location data to improve decisions, create better customer engagement and experiences, reduce risks and automate business processes.
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Published By: SAS     Published Date: Apr 04, 2018
“Fixing health care” is an urgent and pervasive priority for governments, businesses and citizens alike. Within many countries, costs are out of control, resulting in reduced access to quality care for those who need it, higher taxes and/or insurance costs for companies and citizens – and unfortunately, poorer health outcomes.
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Published By: SAS     Published Date: Apr 04, 2018
This white paper, sponsored by SAS, examines the interplay between the challenges and opportunities afforded by the growing breadth of digital channels offered by financial institutions. Mobile wallets, real-time peer-to-peer (P2P), and digital account opening all require the right mix of security solutions, background analytics, and personnel to balance positive customer experience with robust fraud protection. JAVELIN independently produced this whitepaper and maintains complete independence in its data collection, findings, and analysis.
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Published By: SAS     Published Date: May 24, 2018
Ongoing digitization has created vast streams of data, forcing businesses to become more data-driven than ever before. While the benefits of being a data-driven organization are clear (improved performance, more profitability, stronger innovations), there are still some technical and business challenges to overcome. Thanks to technological advancements in data analytics, companies in all types of industries can become data-driven. Read this e-book to discover what it means to be a data-driven organization and to learn the basic do’s and don’ts of how to get there.
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SAS
Published By: SAS     Published Date: May 24, 2018
For 20 years running, SAS has landed a coveted spot on Fortune’s 100 Best Companies to Work For list. Our HR department plays a critical role in keeping current employees engaged and productive as well as anticipating and preparing for future workforce needs. How? One reason is our use of data and analytics to drive HR decision making. It would be easy to assume other companies see the value of analytics; however, a Deloitte survey found 75 percent of HR leaders rate analytics as a priority, yet only 8 percent say their HR organization has a strong analytics capability. I had the pleasure of meeting David Harcourt, Associate Manager of Employee Insights at Yum! Brands when he spoke at the Analytics Experience 2016 conference in Las Vegas. His session, “HR Analytics from Scratch: 8 Lessons Learned in the First Year,” provided valuable insight into what it takes to build HR analytic competency from scratch. His mission is to share with others what he wishes he’d known when he started bui
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Published By: SAS     Published Date: May 24, 2018
Digital transformation is a reality for marketers that is wrapped in both opportunities and headaches. Marketers understand the choices and expectations that their customers now have, and they are up for the challenge. But marketers also have many obstacles to overcome to deliver the consistently good, timely and engaging customer experience, across devices, that customers demand. The good news is that the marketing technology industry is rapidly evolving to address these challenges. And in the same way that consumers have an abundance of choices, marketers also have many options when it comes to choosing partners to help. But where to start, and how to choose the right partners?
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Published By: SAS     Published Date: Jun 06, 2018
Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally. Learn more about key findings, including: Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics. Return on investment for analytics stems from the governing and sharing of data throughout the organization. Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.
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Published By: SAS     Published Date: Jun 06, 2018
Today’s consumers expect immediate, personalized interactions. To meet these expectations, companies must differentiate their brands through timely, targeted and tailored customer experiences based on real-time data analytics. This report, sponsored by SAS, Intel and Accenture and conducted by Harvard Business Review Analytic Services, looks at how businesses are using advanced customer data analytics, along with real-time analytics and real-time marketing, to enhance their customers’ experiences. Learn why organizations that place a high value on real-time capabilities still struggle to achieve them, what companies can do to ensure success as they adopt and implement real-time analytics solutions, and what benefits successful companies are already seeing.
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Published By: SAS     Published Date: Jun 06, 2018
A multitude of “things” generate floods of big data – cars, wearables, machines and appliances. Wouldn’t you like to sift through that noise and become an organization that relies on data to make fact-based decisions? Learn about the three foundations of becoming data-driven – data management, analytics and visualization – and how they can increase profitability, boost performance, raise market share and improve operations. Read about hurdles to becoming a data-driven organization and learn best practices from others. Then get a glimpse of what the future holds with the Internet of Things (IoT), edge analytics, artificial intelligence (AI) and other technology innovations.
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SAS
Published By: SAS     Published Date: Jun 11, 2018
Electric vehicle technology touches all areas of the utility business, including IT, forecasters and grid operations. The growth of IoT-connected devices, both in the utility-owned grid and customer-owned smart energy apps, makes this a rich field for innovation. But what analytics infrastructure is needed in order to manage the future demand coming from EVs? And what opportunities and risks do EVs present? This white paper from Navigant Research, sponsored by SAS and Intel, explores the analytics infrastructure that utilities need to prepare for and benefit from the growth of EVs.
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Published By: SAS     Published Date: Aug 01, 2018
Journey to the Core of Customer Centricity 20 page paper by TM Forum covering: digital transformation in Telco, customer journey analytics, data driven customer experience and real time marketing
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SAS
Published By: SAS     Published Date: Aug 17, 2018
This SAS and Intel collaborated piece demonstrates the value of modernizing your analytics infrastructure using SAS® software on Intel processing. Readers will learn: • Benefits of applying a consistent analytic vision across all functions within the organization to make more insight-driven decisions. • How IT plays a pivotal role in modernizing analytics infrastructures. • Competitive advantages of modern analytics.
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SAS
Published By: SAS     Published Date: Aug 17, 2018
What if we stopped arguing over which analytics software is best, and decided instead to use them all? With today’s analytics technologies, the conversation about open analytics and commercial analytics is no longer an either/or discussion. You can now combine the benefits of SAS and open source analytics within your organization. Download this e-book to learn how businesses in multiple industries are integrating disparate code and information to deploy models and deliver critical results with analytics.
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Published By: SAS     Published Date: Aug 28, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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SAS
Published By: SAS     Published Date: Aug 28, 2018
Machine learning systems don’t just extract insights from the data they are fed, as traditional analytics do. They actually change the underlying algorithm based on what they learn from the data. So the “garbage in, garbage out” truism that applies to all analytic pursuits is truer than ever. Few companies are already using AI, but 72 percent of business leaders responding to a PWC survey say it will be fundamental in the future. Now is the time for executives, particularly the chief data officer, to decide on data management strategy, technology and best practices that will be essential for continued success.
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SAS
Published By: SAS     Published Date: Aug 28, 2018
“Unpolluted” data is core to a successful business – particularly one that relies on analytics to survive. But preparing data for analytics is full of challenges. By some reports, most data scientists spend 50 to 80 percent of their model development time on data preparation tasks. SAS adheres to five data management best practices that help you access, cleanse, transform and shape your raw data for any analytic purpose. With a trusted data quality foundation and analytics-ready data, you can gain deeper insights, embed that knowledge into models, share new discoveries and automate decision-making processes to build a data-driven business.
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SAS
Published By: SAS     Published Date: Aug 28, 2018
With the amount of information in the digital universe doubling every two years, big data governance issues will continue to inflate. This backdrop calls for organizations to ramp up efforts to establish a broad data governance program that formulates, monitors and enforces policies related to big data. Find out how a comprehensive platform from SAS supports multiple facets of big data governance, management and analytics in this white paper by Sunil Soares of Information Asset.
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SAS
Published By: SAS     Published Date: Aug 28, 2018
With the widespread adoption of predictive analytics, organizations have a number of solutions at their fingertips. From machine learning capabilities to open platform architectures, the resources available to innovate with growing amounts of data are vast. In this TDWI Navigator Report for Predictive Analytics, researcher Fern Halper outlines market opportunities, challenges, forces, status and landscape to help organizations adopt technology for managing and using their data. As highlighted in this report, TDWI shares some key differentiators for SAS, including the breadth and depth of functionality when it comes to advanced analytics that supports multiple personas including executives, IT, data scientists and developers.
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SAS
Published By: SAS     Published Date: Oct 03, 2018
Risks have intensified as retailers and financial organizations embrace new technologies to meet customer demands for convenience. The rise of mobile and online transactions introduces new risks – and with that, new requirements for fraud mitigation. This paper discusses key steps for fighting back against fraud risk by establishing appropriate and accurate data, analytics and alert management.
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SAS
Published By: SAS     Published Date: Oct 03, 2018
Fraudsters are only becoming smarter. How is your organization keeping pace and staying ahead of fraud schemes and regulatory mandates to monitor for them? Technology is redefining what’s possible in fighting fraud and financial crimes, and SAS is at the forefront, offering solutions to: • Protect from reputational, regulatory and financial risks. • Reduce the cost of fraud and financial crimes prevention. • Gain a holistic view of risk across functions. • Include cyber events in regulatory report filings. In this e-book, learn the basics in how to prevent fraud, achieve compliance and preserve security. SAS fraud solutions use advanced analytics and artificial intelligence to help your organization better detect and prevent fraud. By applying analytics and powerful machine learning on a unifying platform, SAS helps organizations around the globe detect more financial offenses, reduce false positives and run more efficient investigations.
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SAS
Published By: SAS     Published Date: Nov 16, 2018
Medicaid fraud is prevalent, costly and difficult to prevent. With a combination of more integrated data and advanced analytics, state agencies can turn the tables on fraudsters. They can accelerate the transition from detection to prevention, as new forms of fraud are recognized faster and fewer improper payments go out the door. This IIA Discussion Summary explores the challenges and opportunities in preventing Medicaid fraud in an interview with SAS’ Ellen Joyner-Roberson, Principal Marketing Manager for Fraud and Security Intelligence, and Victor Sterling, Principal Solutions Architect.
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SAS
Published By: SAS     Published Date: Nov 16, 2018
More account openings are taking place through digital devices and online, giving the access and anonymity fraudsters need to steal or fabricate identities. Since credit fraud often starts with a falsified application, it makes sense to have strong tools to monitor loans and credit lines from that point onward. This paper discusses analytics-driven methods for validating applications and spotting trouble at all three stages of bust-out fraud schemes.
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