it analytics

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Published By: SAS     Published Date: Apr 25, 2017
Whether you call them customers, clients, patrons, guests or patients, customers are your organization’s most important asset. And that means customer loyalty should be among your top priorities. No matter when or where the customer journey begins – from websites and online chat to physical locations and call centers – customers expect you to provide a unique and personal experience. How can you use data and analytics to recognize your best customers across channels and know exactly where they are in their customer journey? Keep reading to find out.
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SAS
Published By: SAS     Published Date: May 04, 2017
Should you modernize with Hadoop? If your goal is to catch, process and analyze more data at dramatically lower costs, the answer is yes. In this e-book, we interview two Hadoop early adopters and two Hadoop implementers to learn how businesses are managing their big data and how analytics projects are evolving with Hadoop. We also provide tips for big data management and share survey results to give a broader picture of Hadoop users. We hope this e-book gives you the information you need to understand the trends, benefits and best practices for Hadoop.
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Published By: SAS     Published Date: Jun 05, 2017
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.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
One of the biggest inhibitors of analytics success is the delay between developing and implementing models. This paper reviews how an analytics factory, a rapid scoring and model development environment, can help organizations turn models into insight faster than before.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
As a new era of analytics takes hold, a key characteristic is using analytics to automate IT tasks and decisions. In this Harvard Business Review paper, Tom Davenport describes the opportunity for greater use of analytics in IT, the eras of analytics and how IT will grow and change.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
Data professionals now have the freedom to create, experiment, test and deploy different methods easily – using whatever skill set they have – all within one cohesive analytics platform. IT leaders gain the ability to centrally manage the entire analytics life cycle for both SAS and other assets with one environment. Organizations get faster results and better ROI from analytics efforts.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
Analytics is now an expected part of the bottom line. The irony is that as more companies become adept at analytics, it becomes less of a competitive advantage. Enter machine learning. Recent advances have led to increased interest in adopting this technology as part of a larger, more comprehensive analytics strategy. But incorporating modern machine learning techniques into production data infrastructures is not easy.Businesses are now being forced to look deeper into their data to increase efficiency and competitiveness. Read this report to learn more about modern applications for machine learning, including recommendation systems, streaming analytics, deep learning and cognitive computing. And learn from the experiences of two companies that have successfully navigated both organizational and technological challenges to adopt machine learning and embark on their own analytics evolution.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
Find out what text analytics can do for an organization and the top three things people need to know when adopting text analytics. This research brief from the International Institute for Analytics and SAS outlines the challenges of implementing text analytics solutions and explores what makes this technology unique and exciting.  
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SAS
Published By: SAS     Published Date: Jun 05, 2017
It’s there for the taking – real-time information about every physical operation of a business. All you need is a key: data analytics.  This paper is based on Blue Hill Research’s interviews of three organizations – a US-based oil and gas company, a US municipality and an international truck manufacturer – each of which heavily invested in IoT analytics. Focusing on the key themes and lessons learned from their initiatives, this paper will help business decision makers make informed investment decisions about the future of their own IoT analytics projects.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
The Internet of Things is fast becoming a fixture in some industries, and the technologies for transformative business applications are at hand. Yet many organizations have been slow to recognize and act on these new opportunities. This report from the International Institute for Analytics explores the many business opportunities IoT presents, details its associated implementation challenges and describes how organizations can accelerate their progress so they don’t fall behind.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
From cars to factories to cities, many governments are already collecting information from citizens and connected devices that send and receive data over the internet of things (IoT). While analysts expect the IoT to soar to tens of billions of devices by 2020, no one knows how many or what new types of intelligent devices will emerge. But we do know that traditional approaches to data management and analytics may not be sufficient for sustaining value in this new, connected world
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SAS
Published By: SAS     Published Date: Jun 05, 2017
"The Industrial Internet of Things (IIoT) is flooding today’s industrial sector with data. Information is streaming in from many sources — equipment on production lines, sensors at customer facilities, sales data, and much more. Harvesting insights means filtering out the noise to arrive at actionable intelligence. This report shows how to craft a strategy to gain a competitive edge. It explains how to evaluate IIoT solutions, including what to look for in end-to-end analytics solutions. Finally, it shows how SAS has combined its analytics expertise with Intel’s leadership in IIoT information architecture to create solutions that turn raw data into valuable insights. "
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SAS
Published By: SAS     Published Date: Jun 05, 2017
"As more products and machines become connected, and analytical capabilities grow, new applications for the Internet of Things (IoT) will emerge. So too will manufacturers change how they make business decisions. This IndustryWeek Special Research Report gauges the current and planned usage of IoT technology and analytics by US manufacturers. It also explores how manufacturers can develop a specific IoT strategy and apply analytics more widely across their organizations to drive revenue, cut costs and innovate. "
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SAS
Published By: SAS     Published Date: Jun 05, 2017
"How do you make your brick-and-mortar stores as smart as your website – so when customers walk in the door, you recognize them and cater to their individual tastes? What’s the key to making in-store shopping as frictionless for your customer as online shopping? Read this research summary from the International Institute for Analytics to get started. You’ll learn how to use analytics to gain advanced insight from the Internet of Things: tracking chips, in-store infrared traffic monitors, interactive kiosks and customer mobile devices, to name a few. With analytics, you’ll identify who’s walking in your store, understand their behavior and preferences, and create engaging experiences for your connected customers at every turn. "
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SAS
Published By: SAS     Published Date: Jun 08, 2017
The underground economy is thriving, thanks in part to new technologies and business models such as digital currencies and online marketplaces for freelance services. SAS fraud specialists reveal how government agencies can uncover these activities – and the tax obligations not reported from them. A former head of compliance for the country’s fourth-largest state workers' comp program describes how a comprehensive analytics program found a tax gap of $718 million and was granted funding to double the team’s size without even asking.
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SAS
Published By: SAS     Published Date: Aug 02, 2017
With more data in the hands of more people – and easier access to easy-to-use analytics – conversations about data and results from data analysis are happening more often. And becoming more important. And expected. So it’s not surprising that improved collaboration is one of the most common organizational goals. Why? Because two heads, or 10 heads, are better than one. Because bouncing ideas off of others helps you consider more options. And because sharing what you know may help someone else make better decisions.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
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: Oct 18, 2017
Want to get even more value from your Hadoop implementation? Hadoop is an open-source software framework for running applications on large clusters of commodity hardware. As a result, it delivers fast processing and the ability to handle virtually limitless concurrent tasks and jobs, making it a remarkably low-cost complement to a traditional enterprise data infrastructure. This white paper presents the SAS portfolio of solutions that enable you to bring the full power of business analytics to Hadoop. These solutions span the entire analytic life cycle – from data management to data exploration, model development and deployment.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Quality 4.0 isn't really a story about technology. It's about how that technology improves culture, collaboration, competency and leadership. The last decade has seen rapid advances in connectivity, mo­bility, analytics, scalability and data, creating what some call the fourth industrial revolution, or Industry 4.0. With the help of the Industrial Internet of Things (IIoT), manufacturers have digitized operations, transforming efficiency, supply-chain performance and in­novation. This revolution has even created entirely new business models. This e-book gives manufacturers the tools to lead the Qual­ity 4.0 transformation – a transformation that raises traditional manufacturing to the next level. It teaches readers to use advanced technology, analytics and IIoT to strengthen the manufacturing process and bring it forward into a powerful digital age.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
With the support of SAS, the Internet of Things Institute developed the 2017 Internet of Things ROI Research Study to gather real-world insights, lessons learned and future guidance from current users of IoT technology and advanced analytics. This selective sample of IoT users offers valuable insights to both IoT innovators and organizations still waiting to see how the technology evolves before investing. Multiple business layers and functions have input into IoT decision making. Discover which layer was most critical to success for those organizations that have achieved the highest percentage of their targeted ROI. Learn about the main drivers of success for IoT users achieving higher returns. Lastly, the results highlight six primary factors that can undermine an IoT initiative and how they can be prevented.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Organizations need to accelerate the pace with which they realize business value from data. The focus is on improving “time to value,” which is the length of time it takes from the beginning of a project to the delivery of anticipated business value. This TDWI Best Practices Report focuses on realizing value from BI and analytics and how organizations can accelerate the path to higher value. The report looks at multiple factors impacting the ability of organizations to quickly derive greater value from data and analytics, including the organizational issues, practices, and development methods that are often just as important as keeping pace with technological innovation.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Financial organizations are deploying artificial intelligence and machine learning in the fight against financial crimes. David Stewart, Director of Pre-Sales for the Global Security Intelligence Practice at SAS, offers tips to help separate fact from market hype when reviewing new data analytics tools. You’ll learn about: • The new industry intrigue with artificial intelligence and machine learning. • How these emerging solutions can benefit financial institutions. • The SAS approach of “crawl, walk, run” when it comes to adopting new analytics tools.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Health insurers have long been plagued by issues of fraud, waste, abuse, error and corruption. Taking an enterprise approach to payment integrity – one that combines advanced data management and sophisticated analytics – can help payers detect and prevent fraud; effect positive change in how providers, employees and patients behave; and substantially reduce health care costs. Payers can achieve better outcomes when software support for the core disciplines of payment integrity run on a single platform.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
How much are fraud, error, waste and abuse costing your organization? Costs to insurers are huge – as much as 25 percent of payments made. But data management and analytics can save the day. This paper discusses how data can be used to predict and detect loss in all its forms.
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SAS
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