Experience IBM Watson Order Optimizer
How can retailers efficiently leverage inventory from one channel to serve another without breaking the bank?
See how IBM Watson Order Optimizer helps Fulfillment, Operations, and Inventory:
Gain a holistic view of omni-channel operations across different functional areas
Optimize in real-time against multiple, competing business objectives
Utilize inventory at its most profitable price point
Make better fulfillment decisions with cognitive insights
"Today’s business users want to use all types of data to create compelling, shareable visualizations. But charts and graphs alone may not convey all the information, especially when they are part of a complex series. An audience can best understand analytic results when those results tell a story that connects all the pieces together. The right visuals can also reinforce the lessons buried in the data.
Stories are powerful mechanism to communicate with people. Stories stick and make insights actionable, so it goes without saying that storytelling is a very powerful (soft) skill. In this webinar, you'll learn how to effectively apply storytelling best practices to get your message across. Especially in the world of BI, it is getting more and more important to effectively communicate business results.
Watch this webinar to learn how to use IBM Cognos Analytics to:
· Create the important elements of a good story
· Put the data in context
· Select the best type of ch
"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
Businesses are struggling with numerous variables to determine what their stance should be
regarding artificial intelligence (AI) applications that deliver new insights using deep learning.
The business opportunities are exceptionally promising. Not acting could potentially be a
business disaster as competitors gain a wealth of previously unavailable data to grow their
customer base. Most organizations are aware of the challenge, and their lines of business
(LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
IDC believes that this emerging environment is to date still highly undefined, even as
businesses must make critical decisions. Should businesses develop in-house or use VARs,
systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some
hybrid form? Can they use existing infrastructure, or do AI applications and deep learning
require new servers with new capabilities? We believe that many of these questions can be
Data is the lifeblood of business. And in the era of digital business,
the organizations that utilize data most effectively are also the most
successful. Whether structured, unstructured or semi-structured,
rapidly increasing data quantities must be brought into organizations,
stored and put to work to enable business strategies. Data integration
tools play a critical role in extracting data from a variety of sources and
making it available for enterprise applications, business intelligence
(BI), machine learning (ML) and other purposes. Many organization
seek to enhance the value of data for line-of-business managers by
enabling self-service access. This is increasingly important as large
volumes of unstructured data from Internet-of-Things (IOT) devices
are presenting organizations with opportunities for game-changing
insights from big data analytics. A new survey of 369 IT professionals,
from managers to directors and VPs of IT, by BizTechInsights on
behalf of IBM reveals the challe
As the information age matures, data has become the most
powerful resource enterprises have at their disposal. Businesses
have embraced digital transformation, often staking their
reputations on insights extracted from collected data. While
decision-makers hone in on hot topics like AI and the potential of
data to drive businesses into the future, many underestimate the
pitfalls of poor data governance. If business decision-makers can’t
trust the data within their organization, how can stakeholders and
customers know they are in good hands? Information that is not
correctly distributed, or abandoned within an IT silo, can prove
harmful to the integrity of business decisions.
In search of instant analytical insights, businesses often prioritize data
access and analysis over governance and quality. However, without
ensuring the data is trustworthy, complete and consistent, leaders
cannot be confident their decisions are rooted in facts and reality
Vast resources of data are increasingly available, but the sheer volume can overwhelm human capability. By implementing the cognitive system of IBM Watson Discovery into their infrastructure, businesses can extract deeper and more accurate insights by efficiently identifying, collecting and curating structured and unstructured data.
Watson Discovery, also capable of creating content collections and custom cognitive applications, can transform organizational processes to extend proprietary content and expert knowledge faster and at greater scales.
Read more to learn how Watson Discovery can keep your organization evolving ahead of the competition.
Click here to find out more about how embedding IBM technologies can accelerate your solutions’ time to market.
As cycles accelerate and timelines shorten, projects are being recognized—by necessity— as the delivery arm for strategy. In this environment, anything less than real-time access to real-time project data is too slow, because businesses need to know where they’re heading, not just where they’ve been. CA Project & Portfolio Management (CA PPM 15.3) has added new capabilities to support project, financial and resource management across individual initiatives and entire portfolios. We’ve also built new, embedded BI capabilities that make powerful data and insights more accessible to everyone.
Data and analytics have become an indispensable part of gaining and keeping a competitive edge. But many legacy data warehouses introduce a new challenge for organizations trying to manage large data sets: only a fraction of their data is ever made available for analysis. We call this the “dark data” problem: companies know there is value in the data they collected, but their existing data warehouse is too complex, too slow, and just too expensive to use. A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights.
Key elements of a modern data warehouse:
• Data ingestion: take advantage of relational, non-relational, and streaming data sources
• Federated q
In Q4, 2009, ENTERPRISE MANAGEMENT ASSOCIATES (EMA) analysts worked with ASG to research how executives in IT and within the lines of business use dashboards to gain holistic insights into IT services as they impact business outcomes.
Unlock the benefits of Ethernet – An Expert Q&A Guide provided by Spectrum Enterprise. Find out how technology experts are using reliable Ethernet solutions to boost business performance. Get actionable insights from experts and learn how switching to a high-performance Ethernet solution from Spectrum Enterprise can deliver security and reliability across your network and IT infrastructure.
The competitive advantages and value of BDA are now widely acknowledged and have led to the shifting of focus at many firms from “if and when” to “where and how.” With BDA applications requiring more from IT infrastructures and lines of business demanding higher-quality insights in less time, choosing the right infrastructure platform for Big Data applications represents a core component of maximizing value. This IDC study considered the experiences of firms using Cisco UCS as an infrastructure platform for their BDA applications. The study found that Cisco UCS contributed to the strong value the firms are achieving with their business operations through scalability, performance, time to market, and cost effectiveness. As a result, these firms directly attributed business benefits to the manner in which Cisco UCS is deployed in the infrastructure.
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
This paper explores the results of a survey, fielded in April 2013, of 304 data managers and professionals, conducted by Unisphere Research, a division of Information Today Inc. It revealed a range of practical approaches that organizations of all types and sizes are adopting to manage and capitalize on the big data flowing through their enterprises.
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
Over the course of several months in 2011, IDC conducted a research study to identify the opportunities and challenges to adoption of a new technology that changes the way in which traditional business solutions are implemented and used. The results of the study are presented in this white paper.
Forrester conducted in-depth surveys with 330 global BI decision-makers and found strong correlations between overall company success and adoption of innovative BI, analytics, and big data tools. In this paper, you will learn what separates the leading companies from the rest when it comes to exploiting innovative technologies in BI and analytics, and what steps you can take to either stay a leader or join their ranks.
This white paper, produced in collaboration with SAP, provides insight into executive perception of real-time business operations in North America. It is a companion paper to Real-time Business: Playing to win in the new global marketplace, published in May 2011, and to a series of papers on real-time business in Europe, Asia-Pacific and Latin America.