Read this white paper to get an in-depth look at the benefits of embracing a digital business model, and find out how sports teams of all types can use cloud service providers with digital marketing and analytics tools to gain a competitive edge on the marketing playing field.
Discover what it takes to deliver truly proactive care to customers and find out how active customer experience management can deliver significant business benefits in the form of cost savings, reduced churn, and increased revenue.
Advanced analytics can provide extremelyvaluable insight into today’s media viewers. This must-read report details the top 10 best practices for successfully implementing data analytics for driving profit, attracting new viewers, and increasing viewer loyalty.
Read this report to gain more insights from the Telecoms.com Intelligence survey, and learn why telecommunications operators need analytics to understand their customers—and maintain their loyalty.
Read this whitepaper published by Heavy Reading and sponsored by IBM to look at why network service quality matters to customer loyalty and CSP attitudes to improve it and discover how CSPs can correlate customer loyalty indicators like Net Promoter Scores with network and service quality metrics to help drive better business and operational performance
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.
This white paper discusses the concept of shared data scale-out clusters, as well as how they deliver continuous availability and why they are important for delivering scalable transaction processing support.
This ebook presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences.
Read on to learn more.
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
customer base.
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.
A rewarding customer experience is the central aim for luxury gift company 1-800-Flowers.com: a fast, intuitive shopping process helps keep consumers loyal to its brands. Working with IBM, the company has built a master data management (MDM) system that helps deliver a more seamless experience to shoppers across multiple brands and channels.
Business leaders are eager to harness
the power of big data. However, as the
opportunity increases, ensuring that source
information is trustworthy and protected
becomes exponentially more difficult. If not
addressed directly, end users may lose
confidence in the insights generated from
their data—which can result in a failure to
act on opportunities or against threats.
Information integration and governance
must be implemented within big data
applications, providing appropriate
governance and rapid integration from
the start. By automating information
integration and governance and employing
it at the point of data creation, organizations
can boost confidence in big data.
A solid information integration and
governance program must become a
natural part of big data projects, supporting
automated discovery, profiling and
understanding of diverse data sets to
provide context and enable employees
to make informed decisions. It must be
agile to accommodate a wide variety of
data and seamle
This white paper highlights IBM’s vision for the next-generation data center, its potential to be truly revolutionary and the prescribed pathway for getting there.
An IBM white paper describing the infrastructure implications of today’s converging technology forces and the software defined, next-generation data center transformation vital to capitalizing on them.
Read the white paper to learn how a good data center strategy can help you prepare for the rigors and unpredictability of emerging technologies. Find out how IBM’s predictive analytics are helping companies build more accurate, forward-looking data center strategies and how those strategies are leading to more agile, efficient and resilient infrastructures.
