Analytics has been a hot topic for a long time. In insurance, it's been a core area of focus forever, and descriptive analytics have been followed by predictive analytics. But companies are just beginning to explore prescriptive analytics for decision management, and now comes a whole new era: Cognitive.
Read this white paper to discover how predictive analytics and cognitive commerce make it possible to get instant access to integrated information and actionable insights so you can deliver superior-and profitable-interactions with customers. You'll learn: What it takes to uncover hidden trends and explore relationships across disparate data sources using natural language queries Ways to use in-depth insight to create highly relevant campaigns and content that's aligned with individual customer behaviors and preferences How to take product recommendations to new levels of accuracy with pinpoint prediction and targeting
This white paper discusses how IBM InfoSphere can support the integration and governance of Big Data in healthcare. The white paper reviews three case studies including predictive analytics with Electronic Medical Records, time series data in a neonatal intensive care unit and predictive pathways for disease.
In a recent Aberdeen Group Analyst Insight report,1 Asset Management: The Changing Landscape of Predictive Maintenance, a survey of executives states that the number one risk to operations was failure of their critical physical assets —ensuring that they are available, reliable and performing as originally intended. Though, such a risk can become an opportunity. Top-performing companies rely on analytics related to maintenance, safety and replacement equipment to plan for capital expenditures, manage their assets on a daily basis and maximize asset performance.
IBM offers self-service BI capabilities that tell you what you need to know about the past, present and future—fast. Here are five reasons why you should choose IBM for self-service business intelligence.
Whether you work in marketing, customer service, sales, finance, operations or another area of your business, IBM predictive analytics software puts a wealth of advanced capabilities at your fingertips, anywhere you need them—on premises, on cloud or as a hybrid solution.
Learn why advanced analytics tools are essential to sustain a competitive advantage. This white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics.
Join IBM and partner Zementis in this webcast to hear how Predictive Model Markup Language (PMML), an industry standard, is helping solve business obstacles and enabling users to:
- Drive timely and relevant insights via in-line predictive analytics
- Score thousands of data records per second, scaling with business needs to enable instantaneous decisions
- Improve performance and cost efficiency by reducing or eliminating movement data off-platform to conduct analysis
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
SPSS and open source seamlessly complement each other. With open source, IBM makes it easy to build your own extensions, adding new functionality to existing products. Coding is not required for the use of extensions. IBM offers an extensive library of already developed extensions that can be downloaded and used immediately. Join IBM's open source community and instantly boost your predictive analytics.
It’s hard to grow your business if you can’t see what’s coming next. What will the demand be for a specific product or service and how should you adjust production? What revenue can be expected and from which channels? Where are the best areas to expand your business? Predictive analytics can provide the answers executives, analysts and business managers need to reduce costs, operate more efficiently and increase the bottom line.
Join IBM SPSS and guest Mark Lack, Manager of Strategy Analytics and Business Intelligence with industrial products company Mueller Inc. for a look at how to decrease costs and improve your business’ profitability with predictive analytics. You’ll learn how Mueller extends the value of its Big Data environment by applying predictive techniques to accurately forecast sales, prevent fraud and reduce losses from damaged inventory, saving the company significant time and money.
Businesses today certainly do not suffer from a lack of data.
Every day, they capture and consume massive amounts
of information that they use to make strategic and tactical
decisions. Yet organizations often lack two critical capabilities
when it comes to making the right decisions for the business:
the ability to make accurate predictions about the future,
and to then use those predicted insights in conjunction with
organizational goals to identify the best possible actions they
The combination of predictive analytics and decision
optimization provides organizations with the ability to
turn insight into action. Predictive analytics offers insights
into likely scenarios by analyzing trends, patterns and
relationships in data. Decision optimization prescribes
best-action recommendations given an organization’s
business goals and business dynamics, taking into account
any tradeoffs or consequences associated with those actions.
Predictive analytics is powerful. It can help drive significant improvement to an organization’s bottom line. Look for ways to use it to grow revenue, shrink costs and improve margins.
Provide a platform that enables your data scientists to work efficiently using tools and algorithms they prefer. Enhance your analyses with internal and external data, structured and unstructured data. Then make the analytics accessible in order to reap the full benefits of these valuable analyses.
Stay ahead of the curve in your market with predictive analytics, and give your organization a competitive advantage and an improved bottom line.
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.
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.
Your goal is clear—produce high-quality goods while optimizing resources at every step of production. And in today's uncertain economy, cost-control efforts may never have been more important. Unscheduled downtime because of equipment failure can have a serious impact on your organization's bottom line. Download this white paper from IBM, and learn the basics of predictive maintenance, the benefits it provides manufacturing operations and the underlying technologies that make it possible. Predictive analytics helps you in a number of ways: identify when equipment is likely to fail or need maintenance and take action to maximize up time and reduce future warranty claims costs; optimize allocated labor resources and spare part inventories, helping eliminate undue maintenance, prevent downtime and reduce inventory costs; and determine why certain production runs fail more often than others, identify the cause and analyze whether those runs warrant a recall.
Four technology trends—cloud computing, mobile technology, social collaboration and analytics—are shaping the business and converging on the data center. But few data center strategies are designed with the requisite flexibility, scalability or resiliency to meet the new demands. Read the white paper to learn how a good data center strategy can help you prepare for the rigors and unpredictability of emerging technologies. Find out how IBM’s predictive analytics are helping companies build more accurate, forward-looking data center strategies and how those strategies are leading to more agile, efficient and resilient infrastructures.
Watch this video to see how Denmark’s leading retailer, Coop Danmark, is using predictive analytics and real-time data access to understand customer demand and make more profitable merchandising decisions.