intelligence

This paper introduces the IBM Predictive Customer Intelligence solution, which is designed to help your company create personalized, relevant experiences for individual customers with a focus on driving new revenue.

See how Predictive Customer Intelligence can help identify opportunities to generate revenue, build loyalty, increase wallet share, and improve service.

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.

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.

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. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize

To compete in today’s fast-paced business climate, enterprises need accurate and frequent sales and customer reports to make real-time operational decisions about pricing, merchandising and inventory management. They also require greater agility to respond to business events as they happen, and more visibility into business activities so information and systems are optimized for peak efficiency and performance. By making use of data capture and business intelligence to integrate and apply data across the enterprise, organizations can capitalize on emerging opportunities and build a competitive advantage. The IBM® data replication portfolio is designed to address these issues through a highly flexible one-stop shop for high-volume, robust, secure information replication across heterogeneous data stores. The portfolio leverages real-time data replication to support high availability, database migration, application consolidation, dynamic warehousing, master data management (MDM), service

In the digital era, businesses in every industry are becoming technology companies. New business models such as “product as a service” (in which traditional manufacturers and distributors are driving new revenue streams by integrating software-based services into their offerings) and new operational models, such as collaboration, social business, and mobile platforms, mean that nearly every company is deriving at least part of its revenue from cloudbased solutions. So, why are so many of these new cloud solution providers building their businesses on shaky foundations? The truth is, when your business is based in the cloud, you need more than on-demand leased compute and storage capacity. You need a cloud that is enterprise-grade, secure, and resilient. Equally important—and overlooked by too many cloud solution providers—you need a cloud platform that is able to grow your business into the future, supporting next-generation functionality like Artificial Intelligence (AI). No matter wh

Application-aware vEPC is the key to SDN/NFV service deployments. Deep packet inspection software provides granular network data, which lays the foundation for application awareness in mobile networks. This case study explains how a leading provider of virtualized network solutions uses the best-berforming deep packet inspection (DPI) software R&S®PACE 2 by Rohde & Schwarz to provide their CSP customers with overall network intelligence at a highly granular level.

Research conducted by The Economist Intelligence Unit (EIU), sponsored by Oracle, shows that certain firms are able to consistently demonstrate success in reducing breaches across all major forms of cyber-attack. Read this report to learn more.

Econsultancy’s 2017 Digital Trends report, published in association with Adobe, is based on a global survey of more than 14,000 digital marketing and ecommerce professionals across EMEA, North American and Asia Pacific markets.

Le rapport note cependant que les investissements dans l’analytics sont en perte de vitesse. Apparemment, les entreprises ont tellement à cœur de se prêter au jeu de l’expérience qu’elles ont tendance à s’éparpiller, quitte à négliger l’essentiel.

When it comes to audience engagement, the landscape has been completely rewritten. Media and entertainment companies need to embrace new technologies to achieve revenue goals.

IP data can be used to assess new markets - analysing the vendor landscape and providing insights into future innovation. Using the drones market as an example, we did just that.

US based automobile had multiple ServiceNow instances across multiple companies along with non-standardization of tools and processes. LTI helped in implementing end to end ServiceNow modules including ITSM, ITOM: Orchestration + Event Management thereby achieving high scalability in integrated processes across globe.

i. Brief – US based automobile had no asset management and CMDB discovery which lead to longer procurement lifecycles. LTI implemented end to end ServiceNow and operational support using global delivery model. Also helped in optimising integrations after reviewing license consumptions which then helped in reducing the process implementation to mere 2.5 months ii. Benefits 1. Hybrid process governance helped reduction in TCO by 25% 2. Reduction in number of licenses by 20% using integration with SharePoint

US based Media & Entertainment giant had challenges in multiple integration of 3rd party tools. LTI helped in implementing end to end ServiceNow modules and integration of multiple 3rd party tools like Verizon, Sharepoint, Table API etc which thereby provided higher adoption of portal with enhanced user experience.

Nordics based financial company had challenges in migrating the old legacy network design to Cisco ACI for a new Datacentre. Also it did not had service overview and CMDB to support 150 business services transition. LTI leveraged and implemented several ServiceNow modules, customised 100 odd patterns for 150 business services and executed extensive integration of 25 legacy systems. These transactions and implementation helped in easy cost computation for new business expansions ii. Benefits 1. 25% reduction in DC migration time by creating business service oriented move groups 2. Accurate costing of each business service for replication in new regions/geographies

Your security products send alerts when a cyber attack strikes. Your incident response plan tells you what to do to block the attacker’s action and recover normal operations. But do you know how or where the attacker was able to get into your environment? Do you understand the tactics, techniques and procedures the attacker used? In short, to move to the next level of security, organizations need a way to both understand and manage threat intelligence. Because an organization that can uncover the context of a threat can also better respond to it. Learn more about the impact of security threats from this whitepaper. Join the IBM Security online community to learn from the shared knowledge and experiences of your peers and IBM Cyber Elites to tackle complex business problems.

Data is growing at amazing rates and will continue this rapid rate of growth. New techniques in data processing and analytics including AI, machine and deep learning allow specially designed applications to not only analyze data but learn from the analysis and make predictions. Computer systems consisting of multi-core CPUs or GPUs using parallel processing and extremely fast networks are required to process the data. However, legacy storage solutions are based on architectures that are decades old, un-scalable and not well suited for the massive concurrency required by machine learning. Legacy storage is becoming a bottleneck in processing big data and a new storage technology is needed to meet data analytics performance needs.

Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-fl ash storage infrastructure that is built specifically to work with high-powered analytics.

Interest in machine learning has exploded over the past decade. You see machine learning in computer science programs, industry conferences, and the Wall Street Journal almost daily. For all the talk about machine learning, many conflate what it can do with what they wish it could do. Fundamentally, machine learning is using algorithms to extract information from raw data and represent it in some type of model. We use this model to infer things about other data we have not yet modeled. Neural networks are one type of model for machine learning; they have been around

Everybody’s talking about big data. Huge promises have been made about its role in driving enterprises forward. But few organizations are realizing its true benefits. For those able to put data to good use, there’s much to be excited about. Data is transforming not only businesses, but entire industries, and the world as we know it. Today organizations are harnessing big data to do things like transform healthcare, provide eyesight for the visually impaired, and bringing us closer to autonomous cars

HP Enterprise Security provides a broad view of the vulnerability landscape, ranging from industry-wide data down to a focused look at different technologies, including web and mobile. The goal of this report is to provide the kind of actionable security that intelligence organizations need to understand the vulnerability landscape as well as best deploy their resources to minimize security risk.

HP Enterprise Security provides a broad view of the vulnerability landscape, ranging from industry-wide data down to a focused look at different technologies, including web and mobile. The goal of this report is to provide the kind of actionable security that intelligence organizations need to understand the vulnerability landscape as well as best deploy their resources to minimize security risk. Download this infographic for more info!

Whether critical applications live in the cloud, in the data center, or both, organizations need a point of control for application security. Learn how you can achieve the security, intelligence, and performance that today's infrastructure demands.