Published By: Teradata
Published Date: Jul 07, 2015
As cyber security challenges continue to grow, new threats are expanding exponentially and with greater sophistication—rendering conventional cyber security defense tactics insufficient. Today’s cyber threats require predictive, multifaceted strategies for analyzing and gaining powerful insights into solutions for mitigating, and putting an end to, the havoc they wreak.
It's no longer enough to be able to predict what might happen-organizations also need to know how to respond to predictive insights. This white paper describes how predictive analytics and decision optimization can work together to create a powerful end-to-end decision management system.
The synergy between predictive analytics and decision optimization is critical to good decision making. Predictive analytics offers insights into likely future scenarios, and decision optimization prescribes best-action recommendations for how to respond to those scenarios given your business goals, business dynamics, and potential tradeoffs or consequences.
Together, predictive analytics and decision optimization provide organizations with the ability to turn insight into action—and action into positive outcomes.
In this white paper, you’ll gain a better understanding of:
The difference between predictive and prescriptive analytics
How predictive and prescriptive actions complement one another to help you achieve optimized business decisions
IBM’s approach to creating a powerful end-to-end decision management system
Many companies can't predict which customer they will retain or which customers will increase their spend. With predictive analytics they can.
This knowledge brief from Aberdeeon Group highlights research findings that show organizations which apply predictive analytics are able to:
Establish timely and accurate insights into customer behavior.
Empower employees to do their jobs more effectively.
Encourage more repeat business and higher wallet share
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.
Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
Imagine a world where incident alerts arrive 30 minutes before problems even begin — you’d actually have the power to prevent outages and deliver a truly seamless experience to your customers. Sound impossible? Think again — the right AIOps (Artificial Intelligence for IT Operations) solution can help you maintain uptime, reduce manual incident-management tasks and increase productivity.
IT organizations are now responsible for delivering seamless customer experiences while preventing outages and managing an increasing number of systems. With growing responsibility placed on IT, there is an opportunity to drive strategy for company-wide business processes and operations.
Companies using machine data powered platforms like Splunk collect disparate data types to quickly troubleshoot and monitor systems. By adding predictive capabilities, IT can glean critical insights for the business and develop strategic initiatives on issues that matter.
Download the white paper “Embracing the Strategic Opportunity of IT” to learn how to:
Enable a business aware IT organization
Unlock operational efficiencies
Solve problems with predictive analytics
The world of artificial intelligence (AI) has finally arrived at the doorstep of IT operations. As organizations move toward using both big data and machine learning functionality to support a variety of IT operations, processes and tasks, artificial intelligence for IT operations (AIOps) platforms have emerged as a one-stop solution.
Gartner has released a “Market Guide for AIOps Platforms” that provides findings about the AIOps industry and its latest developments.
Download your complimentary copy to:
*Gain insight into the developing industry of AIOps and its future
*Learn how to optimize IT operations powered by machine learning to drive business value
*Compare different AIOps platform vendors and their range of capabilities
collectd is an open source daemon that collects system and application performance metrics. With this data, collectd then has the ability to work alongside other tools to help identify trends, issues and relationships not easily observable.
Read this e-book to get a deep dive into what collectd is and how you can begin incorporating it into your organization’s environment.
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.
Traditional business intelligence (BI) looks backward at what has happened. In today’s marketplace, enterprises need to look ahead. In this eGuide from TDWI, you'll discover how advances in predictive analytics are enabling organizations to use insights about the past and present to make accurate predictions about the future.
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.
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.
Most CRM systems rely on historical analytics that provide a "rear-view mirror" of your customer relationships, offering little support for the decisions that shape the future. With predictive analytics, you can meet your customers' evolving needs with forward-looking insights that anticipate changes in customer attitudes, preferences, and actions. This white paper from IBM describes how a set of five predictive imperatives can help ensure that your company maximizes the value of its customer relationships and sustains higher levels of revenues and profits.
View this demo to find out how IBM SPSS® solutions for predictive customer analytics can deliver deep customer insights that help you tune your marketing efforts-effectively and efficiently attracting new customers, nurturing customer relationships and retaining ideal customers. Watch how IBM SPSS software uses existing customer information to help you do the following: Identify your best customers for targeted marketing programs with customer segmentation, cluster and profiling techniques; confidently predict which customers will respond to your offers with powerful predictive models; get more out of every customer interaction by delivering real-time, predictive intelligence to front-line decision makers; and enrich and deepen your customer insight with social media analytics.
Data mining uncovers patterns in data through a variety of predictive techniques. By engaging in data mining, organizations like yours gain greater insight into external conditions, internal processes, your markets – and your customers.
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
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
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.