Security managers should evaluate MSSPs for enterprise scale operations, multinational and local presence, and effective threat management and compliance capabilities. Use this Magic Quadrant to evaluate MSSPs to support global service requirements, regional presence and leading-edge services.
Ponemon Institute is pleased to present the results of Uncovering the Risks of SAP Cyber Breaches sponsored by Onapsis. The purpose of this study is to understand the threat of an SAP cyber breach and how companies are managing the risk of information theft, modification of data and disruption of business processes.
Reviewing a year of serious data breaches, major attacks and new vulnerabilities.
The IBM X-Force 2016 Cyber Security Intelligence Index offers a high-level overview of the major threats to businesses worldwide in 2015.
In today’s complex and distributed IT environments, identity and access management (IAM) programs do much more than simply manage user identities and grant access. This paper provides four key steps that can move you toward a more mature solution now.
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
Predictive analytics has come of age. Organizations that want to build and sustain competitive advantage now consider this technology to be a core practice.
In this white paper, author Eric Siegel, PhD, founder of Predictive Analytics World, reveals seven strategic objectives that can only be fully achieved with predictive analytics.
Read this paper to learn how your organization can more effectively:
Compete – Secure the most powerful and unique competitive stronghold
Grow – Increase sales and retain customers competitively
Enforce – Maintain business integrity by managing fraud
Improve – Advance your core business capacity competitively
Satisfy – Meet today's escalating consumer expectations
Learn – Employ today's most advanced analytics
....and finally, render your business intelligence and analytics actionable.
For more and more organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements.
In fact, hybrid cloud is the new norm for IT. IDC says more than 80% of enterprise IT organizations will commit to hybrid cloud by 20171, and 70% of IT decision-makers say they will always have a mix of traditional IT and cloud architectures.2 With important applications and workloads architected across both on-premises and hybrid, public and private cloud environments, business and IT stakeholders must be able to access data with equal efficiency, reliability and speed—regardless of physical location, infrastructure type or time frame.
In this era of digital transformation, business and IT leaders across all industries are looking for ways to easily and cost-effectively unlock the value of enterprise data and use it to deliver new customer experiences while fueling business growth. The digital economy is changing the way organizations gather information, gain insights, reinvent their businesses and innovate both quickly and iteratively.
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business.
The bottom line is that those that have the most customer insight will win because they know what customers want.
So the question is how will you get that insight? What is it that you don’t know about customers in the market(s) that you operate in? Do you have all the attributes about customers in your MDM system that could be of value to your business? Do you know about all the relationships that your customers have in your MDM system?
In most cases, the answer to the above questions is no which inevitably means one thing. You need more data
Today, all consumers can obtain any piece of data at any point in time. This experience represents a significant cultural shift: the beginning of the democratization of data.
However, the data landscape is increasing in complexity, with diverse data types from myriad sources residing in a mix of environments: on-premises, in the cloud or both. How can you avoid data chaos?
As with most innovations in business information technology, the ultimate truth about cloud lies somewhere in between. There is little doubt that cloud-based infrastructures offer an immediate opportunity for smaller organizations to avoid the costly investment needed for a robust on-premises computing environment. Data can be found, processed and managed on the cloud without investing in any local hardware. Large organizations with mature on-premises computing infrastructures are looking to Hadoop platforms to help them benefit from the vast array of structured and unstructured data from cloud-based sources. Organizations have feet in both cloud and on-premises worlds. In fact, one could easily argue that we already live in a “hybrid” world.
Cloud- based data presents a wealth of potential information for organizations seeking to build and maintain competitive advantage in their industries. However, as discussed in “The truth about information governance and the cloud,” most organizations will be challenged to reconcile their legacy on- premises data with new third- party cloud- based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
A solid information integration and governance program must become a natural part of big data projects, supporting automated discovery, profiling and understanding of diverse data sets to provide context and enable employees to make informed decisions. It must be agile to accommodate a wide variety of data and seamlessly integrate with diverse technologies, from data marts to Apache Hadoop systems. And it must automatically discover, protect and monitor sensitive information as part of big data applications.
High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-c entric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain a competitive advantage in their industry. However, as discussed in “The truth about information governance and the cloud,” most organizations will be confronted with the challenging task of reconciling their legacy on-premises data with new, third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
Download this eBook to learn:
- How the use of advanced analytics generates powerful insights to stay ahead of evolving cyber threats
- Why Cyber Threat Analysis is the most effective defensive strategy
- How analysts benefit from the use of sophisticated data visualization to identify hidden threat relationships and patterns
- Why shifting from attack prevention to mitigation is a more practical goal for commercial organizations
Download this white paper to learn:
- How the use of advanced analytics generates powerful insights to stay ahead of evolving cyber threats.
- Why security infrastructure protection alone is not enough to thwart cyber criminals, and how you can fortify your existing security strategy.
- How the use of both machine led analytics with human led analysis can help you mitigate threats.
As traditional network perimeters surrounding data centers dissolve, agencies face enormous difficulties fending off attacks using a patchwork of traditional security tools to protect classified or personally identifiable information (PII). Time and again, traditional security practices have proven porous and/or unsustainable.
Read this i360Gov Book to understand the importance of:
- Transforming federal fortifications into intelligence-driven defense
- Intensifying focus on cyber intelligence
-Needing a well trained cybersecurity force