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
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
Published By: Teradata
Published Date: Jan 28, 2015
Althrough Hadoop and related technologies have been with us for several years, most business intelligence (BI) professionals and their business counterparts still harbor a few misconceptions that need to be corrected about Hadoop and related technologies such as MapReduce.
This webcast presents the 10 most common myths about Hadoop, then corrects them. The goal is to clarify what Hadoop is and does relative to BI, as well as in which business and technology situations Hadoop-based BI, data warehousing and analytics can be useful.
Privileged user accounts—whether usurped, abused or simply misused—are at the heart of most data breaches. Security teams are increasingly evaluating comprehensive privileged access management (PAM) solutions to avoid the damage that could be caused by a rogue user with elevated privileges, or a privileged user who is tired, stressed or simply makes a mistake. Pressure from executives and audit teams to reduce business exposure reinforces their effort, but comprehensive PAM solutions can incur hidden costs, depending on the implementation strategy adopted. With multiple capabilities including password vaults, session management and monitoring, and often user behavior analytics and threat intelligence, the way a PAM solution is implemented can have a major impact on the cost and the benefits. This report provides a blueprint for determining the direct, indirect and hidden costs of a PAM deployment over time.
Privileged user accounts—whether usurped, abused or simply misused—are at the heart of most data
breaches. Security teams are increasingly evaluating comprehensive privileged access management (PAM)
solutions to avoid the damage that could be caused by a rogue user with elevated privileges, or a privileged
user who is tired, stressed or simply makes a mistake. Pressure from executives and audit teams to reduce
business exposure reinforces their effort, but comprehensive PAM solutions can incur hidden costs,
depending on the implementation strategy adopted. With multiple capabilities including password vaults,
session management and monitoring, and often user behavior analytics and threat intelligence, the way a
PAM solution is implemented can have a major impact on the cost and the benefits. This report provides a
blueprint for determining the direct, indirect and hidden costs of a PAM deployment over time.
Today’s IT professionals are well aware that users expect fast, reliable access to ever-growing amounts of data – from web content, to videos, to business intelligence data and more. Meeting the challenges of this exponential growth is nearly impossible with existing, spinning media storage technology. Hard disk drives (HDDs) have been the standard in data storage for decades, but they can no longer satisfy. They create bottlenecks in data access, they fail to meet the growing demands of higher user expectations, and they consume too much power. Download to learn how to solve this issue.
Published By: Attunity
Published Date: Feb 12, 2019
Read this checklist report, with results based on the Eckerson Group’s survey and the Business Application Research Center (BARC), on how companies using the cloud for data warehousing and BI has increased by nearly 50%. BI teams must address multiple issues including data delivery, security, portability and more before moving to the cloud for its infinite scalability and elasticity.
Read this report to understand all 7 seven considerations – what, how and why they impact the decision to move to the cloud.
Ask the average business user what they know about Business Intelligence (BI)
and data analytics, and most will claim to understand the concepts. Few, however,
will profess to know how analytics works or to have the skills needed to put it
into practice. Despite being knowledgeable about their industry and experienced
in running their organizations, the majority of business users lack expertise in
analytics and visualization techniques—but that doesn’t stop them from wanting
to have a go.
This situation has led to ease of use and accessibility becoming the main focus
for recent updates from all the leading BI vendors—but making tools easier and
more widely accessible is only part of the answer.
A better approach is to work both sides of the gap. To make tools that can
empower business users to discover and unlock value in their data—and that
extend capabilities for experts, so they can share the analytics workload, improve
efficiency, and focus on higher level work.
Location has become paramount to building new apps, services, experiences and business models. If data is the new oil, then location is the crude oil. This is why most of the top location platform players have been developing technologies to power next-generation autonomous mobility systems. And the “richness” of location data and real-time intelligence are becoming strong monetization opportunities.
The 2018 Counterpoint Research Location Ecosystems Update compared 16 location platform vendors, including Google, TomTom and Mapbox. Learn why the HERE Open Location Platform – described as super-rich, always up-to-date, and a neutral offering – is a leader in the location data arena.
Published By: Netsuite
Published Date: Jul 24, 2017
Baseball has always collected in-game data.
However, until recently, fans didn’t have easy
access to the various statistics that coaches
used for key decisions important for the
development of the players and success on
the baseball field.
It’s not unlike how traditional business
intelligence is delivered. Data and reports are
set aside for a few experts who determine
what is important for you.
Today, baseball statistics are widely available
during broadcasts on TV, PCs and mobile
devices. Basic data displays like inning and
score are enhanced with metrics meaningful
to students of the game, such as pitch speed,
strikeout percentages and hit zones. It’s a good
example of vital information being delivered in
real-time, on demand and in context.
Business intelligence analytics streamline the task of gathering critical data across the health care enterprise and turns it into readily accessible, actionable information. Health care business intelligence is a package of software and services that offers clarity on and control over the vast amount of data needed to successfully run a medical organization.
This Economist Intelligence Unit report discusses how highgrowth small and mid-sized enterprises (SMEs) are scaling their organisations to provide resources for growth whilst ensuring flexibility to respond quickly to changes in market conditions; the role of technology in scaling SMEs; and success factors in scaling headcount.
As businesses start to experiment with true artificial intelligence, safe delivery of AI demands a new risk and control framework. This report, designed for anyone tasked with the safe delivery of AI, proposes an effective solution.
Read the report to find out:
• the risks associated with AI and the challenge of managing them
• a 17-category Risk & Controls framework for AI
• in-depth details for key categories, including security management, business continuity and knowledge management
• an essential glossary of AI terms.
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.
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.
This video demonstrates how IBM’s Behavior Based Customer Insight for Banking leverages predictive analytics to help you personalize customer engagement and deliver customized actions. The solution leverages advanced predictive models to analyze customer transactions and spending behavior to more deeply understand customer needs and propensities, anticipate life events, and help provide a unique customer experience.
Learn new ways of analyzing digitally connected customers-from dynamic segmentation to the use of advanced analytics. With predictive tools, banks can analyze transactions and spending behavior to better understand customer needs, anticipate life events, and provide a unique experience.
Forward-looking enterprises know there's more to big data than strong and managing large volumes of information. Big data presents an opportunity to leverage analytics and experiment with all available data to derive value never before possible with traditional business intelligence and data warehouse platforms. Through a modern, big data platform that facilitates self-service and collaborative analytics across all data, organizations become more agile and are able to innovate in new ways.
Competitive enterprises that embark on big data strategies do so with the expectation that their businesses will transform. They don't just want answers from the data they collect and analyze, they want results. Be it with small, fledgling trials or large, cross-functional efforts, these enterprises want to see clearly how big data can make a difference - with their customers, their processes, their bottom lines and, most important, with growing the business.
ERP and Business Intelligence are essential to your success. Read this and learn how to improve productivity and decision-making. You'll see how Blue Coat WAN Optimization leverages proven solutions to achieve dramatic reductions in latency and bandwidth consumption.