it analytics

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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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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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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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SAS
Published By: SAS     Published Date: Dec 20, 2018
Think of the self-service things you use in a day. Gas pumps. ATMs. Online apps for shopping. They’re convenient and easy to use. People choose what they want, when they want – without involving others in their minute-to-minute decisions. What if your organization could treat data discovery and analytics the same way? SAS has combined two of its visual solutions to do just that. SAS Visual Analytics and SAS Visual Statistics share the same web-based interface to provide self-service data exploration and easy-to-use interactive predictive analytics in a collaborative environment. This white paper takes a look at this convergence and outlines how these products can be used together so that everyone, even nontechnical users, can investigate data on their own, create analytical models and uncover new insights that drive competitive differentiation. Your analytics journey just got a lot easier.
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SAS
Published By: SAS     Published Date: Dec 20, 2018
Data professionals now have the freedom to create, experiment, test and deploy different methods easily using whatever skill set they have and 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. Organisations get faster results and better ROI from analytics efforts.
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SAS
Published By: SAS     Published Date: Jan 04, 2019
How can you open your analytics program to all types of programming languages and all levels of users? And how can you ensure consistency across your models and your resulting actions no matter where they initiate in the company? With today’s analytics technologies, the conversation about open analytics and commerical analytics is no longer an either/or discussion. You can now combine the benefits of SAS and open source analytics technology systems within your organization. As we think about the entire analytics life cycle, it’s important to consider data preparation, deployment, performance, scalability and governance, in addition to algorithms. Within that cycle, there’s a role for open source and commercial analytics. For example, machine learning algorithms can be developed in SAS or Python, then deployed in real-time data streams within SAS Event Stream Processing, while also integrating with open systems through Java and C APIs, RESTful web services, Apache Kafka, HDFS and more.
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Published By: SAS     Published Date: Jan 04, 2019
As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment. Newer examples of operational analytics include support for logistics, customer call centers, fraud detection, and recommendation engines to name just a few. Embedding analytics is certainly not new but has been gaining more attention recently as data volumes and the freq
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SAS
Published By: SAS     Published Date: Jan 30, 2019
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: Mar 20, 2019
What’s on the chief data and analytics officer’s agenda? Defining and driving the data and analytics strategy for the entire organization. Ensuring information reliability. Empowering data-driven decisions across all lines of business. Wringing every last bit of value out of the data. And that’s just Monday. The challenges are many, but so are the opportunities. This e-book is full of resources to help you launch successful data analytics projects, improve data prep and go beyond conventional data governance. Read on to help your organization become truly data-driven with best practices from TDWI, see what an open approach to analytics did for Cox Automotive and Cleveland Clinic, and find out how the latest advances in AI are revolutionizing operations at Volvo Trucks and Mack Trucks.
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SAS
Published By: SAS     Published Date: Mar 20, 2019
Seeing value from analytics and emerging technologies such as AI begins with trust in the data. That trust relies on how data is collected, shared, protected and used. The annual Data and Analytics Global Executive Study with MIT Sloan Management Review looks at how 2,400 global business leaders make decisions based on analytics insights – and what steps are needed to get trustworthy data.
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SAS
Published By: SAS     Published Date: Mar 20, 2019
In today’s crowded analytics marketplace, who can you trust? What’s needed to deliver on the promise of transforming data into real value? And what do CIOs need to cost-effectively and successfully lead their organizations through changing technologies? For an organization to experiment with (and ultimately deploy) analytics, the responsibility falls squarely on the shoulders of IT. IT must provide secure access to lots of high-quality data, a friendly environment for experimentation and discovery, and a method for rapidly deploying and governing models. SAS can support an organization's journey toward becoming a data- and analytics-driven organization. We can help unlock the value by enabling with choices that make sense. Plus, we can show organizations how to get the most out of technology investments.
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SAS
Published By: SAS     Published Date: Apr 17, 2019
Organizations are charging ahead with investments in cloud and analytics to deliver agility, scalability and cost savings. With computing power advancements and continuous growth of data, cloud provides the elastic workloads and flexibility required for modern business. However, the environment of flexibility and choice that cloud provides also creates complexity and challenges. In this white paper, learn how organizations are applying expertise and using the latest methods to move analytics to the cloud, including: Why are organizations moving analytic work to the cloud? What are the key challenges and misconceptions? How do IT leaders provide choice while maintaining control?
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SAS
Published By: SAS     Published Date: Jun 26, 2019
From child welfare and public health to combating prescription abuse and improving education, analytics is improving government programs around the world. The articles in this e-book touch on several areas where analytics is making, or could make, a significant impact in the way governments operate. We’ve pulled together some of our favorite best practices that showcase the role analytics plays in better decision making.
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SAS
Published By: SAS     Published Date: Jun 26, 2019
To support open government initiatives and uphold the values of transparency, participation and collaboration in the US, federal agencies today make their data open, or publicly accessible. Citizens can use this open data to assess college affordability, the economy, educational issues, environmental damage, health care, taxes, agriculture, the climate and more. Governments can use APIs to pull this open data into SAS Visual Analytics as a way to identify trends and patterns and obtain all sorts of new insights. With public health surveillance, for example, governments can monitor and evaluate indicators that point to high-risk areas so they’ll know where and how to focus efforts. Such public health surveillance can serve as an early warning system for impending emergencies, document the impact of an intervention, track progress toward public health goals, and clarify health problems to inform public health policies and strategies.
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SAS
Published By: SAS     Published Date: Jun 27, 2019
In the quest to understand how a therapeutic intervention performs in actual use – in real medical practice outside the controlled environment of clinical trials – many life sciences organizations are stymied. They rely on one-off processes, disconnected tools, costly and redundant data stores, and ad hoc discovery methods. It’s time to standardize real-world data and analytics platforms – to establish much-needed consistency, governance, repeatability, sharing and reuse. The organizations that achieve these goals will formalize their knowledge base and make it scalable, while significantly reducing turnaround times, resources and cost. Learn the seven key components for putting that structure to real-world evidence – and four ways to take it to the next level.
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SAS
Published By: SAS     Published Date: Jun 27, 2019
The potential for analytics to transform health care – to make it more personalized, intelligent, cost-efficient and effective – is immense. The question is, how will you move your organization forward to exploit the power of analytics? In this paper, explore recommendations and best practices from experts at UnitedHealth Group, Eli Lilly and Company, and Mercy Virtual who are operationalizing SAS analytics across their enterprises and realizing impressive results.
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SAS
Published By: SAS     Published Date: Jul 22, 2019
Text is the largest human-generated data source. It grows every day as we post on social media, interact with chatbots and digital assistants, send emails, conduct business online, generate reports and essentially document our daily thoughts and activities using computers and mobile devices. Increasingly, organizations want to know how all of that data can be used to drive improvements. For many, unstructured text represents a massive untapped data source with great potential for producing valuable insights that could result in significant business transformations or spur incredible social innovation. This paper looks at how organizations in banking, health care and life sciences, manufacturing and government are using SAS text analytics to drive better customer experiences, reduce fraud and improve society.
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SAS
Published By: SAS     Published Date: Aug 06, 2019
Under risk adjustment, health plans with a lower average risk score make payments into the system or miss out on revenue opportunities, while plans with relatively high average risk scores receive payments. So it’s critical for a plan to get this analysis right – or forfeit revenue it deserves. With advanced analytics and machine learning, health care organizations can be more timely and confident in their risk adjustment programs, more effectively managing the cost of care and building a stable annual financial portfolio.
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