Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
IBM Institute for Business Value report discussing how multicloud environments are proliferating in surveyed organizations, the benefits of multicloud management and an approach to managing multicloud environments
A new era of business reinvention is dawning. Organizations are facing an unprecedented convergence of technological, social and regulatory forces. As artificial intelligence, automation, Internet of Things, blockchain and 5G become pervasive, their combined impact will reshape standard business architectures. The “outside-in” digital transformation of the past decade is giving way to the “inside-out” potential of data exploited with these exponential technologies.
We call this next-generation business model the Cognitive Enterprise.
An opportunity for Chief Procurement Officers (CPOs): As business models evolve and technology advances, CPOs can elevate their value across enterprises and extended supplier networks with Cognitive Procurement capabilities that can sense and act.
Empowering the Automotive Industry through Intelligent Orchestration
With the increasing complexity and volume of cyberattacks, organizations must have the capacity to adapt quickly and confidently under changing conditions. Accelerating incident response times to safeguard the organization's infrastructure and data is paramount. Achieving this requires a thoughtful plan- one that addresses the security ecosystem, incorporates security orchestration and automation, and provides adaptive workflows to empower the security analysts.
In the white paper "Six Steps for Building a Robust Incident Response Function" IBM Resilient provides a framework for security teams to build a strong incident response program and deliver organization-wide coordination and optimizations to accomplish these goals.
IBM provides a security incident response (IR) solution called Resilient
that helps its customers address security incidents quickly in an automated
and orchestrated manner. IBM commissioned Forrester Consulting to
conduct a Total Economic Impact™ (TEI) study and examine the potential
return on investment (ROI) enterprises may realize by deploying Resilient.
The purpose of this study is to provide readers with a framework to
evaluate the potential financial impact of the Resilient platform on their
If your bank is like many, it encrypts only a minimum of data. This is because many banks believe, incorrectly, that encrypting all data is unworkably cost- and resource-intensive on any platform. Encrypting piecemeal creates the need to carefully track where you are encrypting, what you are encrypting, and the time and resource costs of these activities.
It’s probably no surprise to you that the financial services industry is changing rapidly. Digital technology is redefining the possibilities with automated processes, AI insights, customized experiences, new operating models and next-generation applications — yet global industry profits are stagnating. As the number of disruptors in the space rises, many banks are being asked to innovate while lowering structural costs and improving capital returns — and many traditional banks are falling behind.
As more companies transform their infrastructures with hybrid cloud services, they require environments that protect the safety of their intellectual property, such as data and business rules. In addition, businesses need a set of hybrid cloud services that provides the best of both worlds: the elasticity and automatic provisioning of the public cloud with the economic viability of the private cloud. Welcome to IBM LinuxONE.
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 our 29-criteria evaluation of machine learning
data catalogs (MLDCs) providers, we identified
the 12 most significant ones — Alation,
Cambridge Semantics, Cloudera, Collibra,
Hortonworks, IBM, Infogix, Informatica, Oracle,
Reltio, Unifi Software, and Waterline Data —
and researched, analyzed, and scored them.
This report shows how each provider measures
up and helps enterprise architecture (EA)
professionals make the right choice.
The growing need for data governance, risk and compliance, data analysis and data value still drives strategic requirements in metadata management and the growth of its solutions. Data and analytics leaders can use this vendor evaluation to find the most appropriate solution for their organization.
In this report, we''ll analyze the many challenges that organizations face when it comes to building and managing modern IT infrastructure. We'll also look at how many businesses are taking advantage of a hybrid cloud and on-premise approach, which comes with some significant benefits.
There can be no doubt that the architecture for analytics has evolved
over its 25-30 year history. Many recent innovations have had significant
impacts on this architecture since the simple concept of a single
repository of data called a data warehouse. First, the data warehouse
appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the
traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had
a substantial effect on the analytical architecture.
In Forrester's evaluation of the emerging market for conversational computing platforms, we identified the seven most significant providers — Amazon, Google, IBM, Microsoft, Nuance Communications, Oracle, and Rulai — in the category and evaluated them. This report details our findings about how each vendor scored against nine criteria and where they stand in relation to each other. Application developers should use this review to select the right partners for their conversational computing platform needs.
Delivering personalized customer experience remains the top business challenge for communications
service providers (CSPs). Ovum's recently published 2018 ICT Enterprise survey saw almost all CSP
IT executives interviewed identify delivering personalized customer experience as one of their three
most important business challenges for the next 18 months. This trend emphasizes the high priority
CSPs place on how customer relationships are managed. However, several factors have an impact on
CSPs' ability to identify and then deliver customers' core needs. These include understanding the data
sets they should focus on; collecting, cleansing, and consolidating these data sets; and having the
right expertise to mine the data sets.
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 strongly believes that the days of homogenous compute, in which a single architecture dominates all
compute in the datacenter, are over. This truth has become increasingly evident as more and more
businesses have started to launch artificial intelligence (AI) initiatives. Many of them are in an
experimental stage with AI and a few have reached production readiness, but all of them are cycling
unusually fast through infrastructure options to run their newly developed AI applications and services on.
Power Systems are built for the most demanding, data-intensive, computing
on earth. Our cloud-ready servers help you unleash insight from your
data pipeline—from managing mission-critical data, to managing your
operational data stores and data lakes, to delivering the best server for
POWER9 provides the infrastructure foundation for a future-looking
organization that is ready to meet today’s business challenges and tomorrow’s
advancements. By updating your foundation with the latest POWER9-based servers,
you can effectively run your mission-critical requirements alongside modern, dataintensive workloads. POWER9 gives you the reliability you’ve come to trust from
IBM Power Systems, the security you need in today’s high-risk environment, and the
innovation to propel your business into the future.
The data maturity curve
As companies invest more and more in data access and
organization, business leaders seek ways to extract more
business value from their organization’s data.
92 percent of business leaders say that to compete in the future,
their organization must be able to exploit information much more
quickly than it can today.1
Chief Information Officers (CIO) need solutions that will allow
them to evolve their organization’s approach to data and drive real
value with strategic decisions. This journey can be depicted in
a data maturity curve.