Overwhelmed by the volume of security intelligence and alerts, human analysts need machine learning to augment and accelerate efforts. Machine learning moves security analytics from diagnostic and descriptive to prescriptive and proactive, leading to faster and more accurate detection.
Hear a panel of HR leaders engage in a conversation about how they are using predictive and prescriptive analytics applied to talent to drive better business results. Join us to explore how you can be more effective in designing pilots, demonstrating the ROI for talent analytics, and translating talent data into talent insight.
Companies are becoming more analytically mature and are developing greater analytical capabilities. Many companies are also creating a context for analytics, with analytical cultures and processes. When companies compete based on analytics, analytics is having a positive bottom-line impact.
Published By: TeamQuest
Published Date: Dec 19, 2014
Businesses are constantly putting pressure on price, performance and reliability of IT services and infrastructure. Recent adoption of technologies such as virtualization, dynamic computing and various forms of cloud computing coupled with changing management paradigms has raised the stakes even more. This ruthless drive for efficiency calls for the use of more sophisticated optimization methods. It is safe to say that if you don’t, chances are you will be “done” by others who do.
Published By: Tripwire
Published Date: Dec 16, 2009
This Prescriptive Guide outlines the steps information security managers can take to break the compliance blame cycle and build an information security program that works. It also describes how they can achieve alignment among all stakeholders so that information security and compliance activities become integrated into daily business operations.
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.
Many organizations and agencies would like to improve their debt collection. They are aware that advanced analytics can help them optimize collections to drive down company debt and collection expenditures. However, they perceive that advanced analytics requires massive infrastructure changes, expensive software licenses, analytics expertise, long lead times and major upfront capital expenses.
Life revolves around prediction—for example, the route you take to get to work, whether to go on a second date, or whether or not to keep reading this sentence are all forms of prediction. We are already seeing machine learning powered by Apache Spark changing the face of innovation at IBM. Learn more.
In this paper – which is based on a webinar hosted by the Direct Marketing Association (DMA) and sponsored by SAS – we will take a look at how these technological advancements can enable you to become more predictive and prescriptive in your digital and integrated marketing efforts.
Traditionally, business intelligence (BI) has looked backward at what has happened. In today’s marketplace, enterprises need to look ahead. From predictive to prescriptive intelligence, TDWI and IBM look at what businesses need most.
As any line of business (LOB) leader knows, making customer level decisions that balance risk and profit just keeps getting harder. And even when you think you have the right decisions, turning them into actions can be even trickier. You also need to consider the factors that make smart decisions difficult. Big data. Regulations. Customers who want an offer, fast, or else you’re going to lose them.
As consumers, we’re all having more experiences that seem almost magical:
You’re in a mall when suddenly your smartphone beeps. It’s an offer for 20% off a pair of shoes you’ve been looking at online — from the store you just walked past!
As business people, we know it’s not magic, but rather analytics powering these outstanding customer experiences.
Analytics have evolved to the point where they answer an expanding range of useful questions. But understanding the different types of analytics – descriptive, diagnostic, predictive and prescriptive - and how to use them in your business can be challenging.
Download the eBook to learn about the least understood – yet most powerful – tool in the analytic arsenal.
Prescriptive analytics enable you to estimate and compare the likely outcomes of any number of actions, and choose the very best action to advance business objectives. Getting there isn’t as difficult as you think.
Start your journey. Download the eBook today.
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