This ESG Lab report presents the results of a mixed workload performance benchmark test designed to assess the real world performance capabilities of an IBM Storwize V7000 storage system and IBM x3850 X5 servers in a VMware-enabled virtual server environment.
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
Analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of Big Data. Learn more about how Big Data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs. Access the report now.
Is your data architecture up to the challenge of the big data era? Can it manage workload demands, handle hybrid cloud environments and keep up with performance requirements? Here are six reasons why changing your database can help you take advantage of data and analytics innovations.
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
With the advent of big data, organizations worldwide are
attempting to use data and analytics to solve problems previously
out of their reach. Many are applying big data and analytics
to create competitive advantage within their markets, often
focusing on building a thorough understanding of their
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-centric
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.
Published By: IBM APAC
Published Date: May 14, 2019
Clients can realize the full potential of artificial intelligence (AI) and analytics with IBM’s deep industry expertise, technology solutions and capabilities and start to infuse intelligence into virtually every business decision and process. IBM’s AI & Analytics Services organization is helping enterprises get their data ready for AI and ultimately achieve stronger data-driven decisions; access deeper insights to provide improved customer care; and develop trust and confidence with AI-powered technologies focused on security, risk and compliance.
Artificial intelligence (AI) is moving beyond the hype cycle, as more and more organizations seek to adopt AI-related technologies. These organizations are focusing on prioritizing functional areas and use cases, placing a stronger emphasis on topline growth, taking up a renewed interest in their data infrastructure and articulating greater unease about the skills of their knowledge workers. This report explores how they are approaching str
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.
This paper explores why your business needs the latest operational decision management (ODM) solutions to help turn data insights into action. Discover how IBM Operational Decision Manager software and the IBM Business Process Manager platform work together to: *Recognize patterns that suggest opportunity or risk *Create and shape business events by automating decisions *Bring more dimension and precision to decision making by applying analytics to big data *Help you implement the right business processes by understanding data in context.
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.
The new frontier for personalized customer experience: IBM Predictive Customer 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. Along with explaining the architecture of the solution, this paper covers how the solution works.
In this report you will learn how to enhance your customer relationships across all your channels and touch points, produce personalized customer offers and learn from real-world case studies across various industries.
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.
The Smarter Process platform is IBM’s solution for reinventing
business operations in a way that infuses every process
with intelligence and expertise to deliver greater customer
centricity, which in turn fuels top-line growth. It incorporates
Business Process Management, Case Management,
Operational Decision Management and Process Analytics,
along with Process Discovery and Design with an objective of
ensuring that customers find it easy to do business and that
every interaction includes positive touch points.
Within the context of this new imperative, accessing cloud
efficiencies, leveraging mobile for greater engagement,
mining big data for insights, and enhancing customer
relationships via social media, are proving to be critical and
Thrill customers and empower employees with omni-channel, socially-infused digital experiences to drive better business outcomes
IBM Customer Experience Suite features rich, integrated capabilities for managing web content, rich-media assets, real-time social communications, robust customer self-service capabilities, business analytics and mobile device delivery
IBM Employee Experience Suite enables employees to easily find and share relevant information across multiple platforms, diverse geographies with multiple languages, and within the context of business applications
"What would you do if you didn’t have to rely on disparate analytics solutions to meet the needs of business users while following the rules of IT?
View this 'Charting Your Analytical Future' webinar to learn about a world of innovation and independence for users that does not limit the confidence and controls of IT.
With the cognitive-guided self-service features available in IBM business analytics solutions, more users than ever before can get the answers they need. Next-generation business analytics capabilities make it possible to access relevant data, prepare it for analysis and understand performance. But it doesn’t stop there. Users can package the results in a visually-appealing format and share them throughout the organization.
Don’t miss this opportunity to hear how you can:
* Benefit from advanced analytics without the complexity
* Operationalize insights and dashboards from a collection of trusted data sources
* Tell your story with rich visualizations and geospati
Download this paper written by BPM partners to see how the 'last mile' has become a very complex and challenging process for companies and their CFO's and the strategic need to automate the controls around these processes.