Aberdeen has long illustrated the benefits of well-managed, trustworthy data, and the problems associated with poor data quality. As data volumes rapidly expand and data environments become more complex, what were once small nuisances evolve into massive, company-wide problems. In order to avoid these pitfalls and achieve better business efficiency and operational performance, top performing organizations have found it necessary to invest in tools such as data security, master data management, data quality, data lifecycle management and data integration. Using research collected from December 2009 to December 2012, Aberdeen examines the hidden financial penalties for lapsed information governance and untrustworthy data.
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Learn how IBM Business Analytics software supports organizations when accessing big data, interacting with it to discover and visualize patterns and trends, and performing advanced analytics.
The arrival of big data into the enterprise has had a major impact on enterprise information protection as new data stores have emerged, increasing the distribution of data and the complexity of securing and protecting that data along with it. Big data has forced companies to have to define new requirements when it comes to both data management and enterprise information protection. It is now harder to protect sensitive data as it may move around between different transactional and analytical data stores as companies create new analytical workloads. Read this paper by Mike Ferguson of Intelligent Business Strategies to learn how IBM System z can help secure your data.
Cost/Benefit Case for IBM PureData System for Analytics: Comparing Costs and Time to Value with Teradata Data Warehouse Appliance
Three-year costs of ownership for use of PureData System for Analytics N2001 appliances average 36 percent less than for Teradata equivalents. Comparisons are for comparable applications and workloads. This report applies both sets of metrics to cost comparisons for IBM PureData System for Analytics N2001 and Teradata Data Warehouse Appliance 2700 in four representative installations in digital media, financial services, retail and telecommunications companies. Results are based on input from 17 organizations employing Teradata Data Warehouse Appliances and 21 employing IBM PureData System for Analytics appliances in comparable roles.
Big data is already being collected by many government organizations— and new data is being generated at rapidly accelerating rates. The ability to perform analytics on big data enables government organizations to improve existing processes and operations, and engage in entirely new types of analyses that weren’t possible before.
Organizations in the petroleum industry are no strangers to large volumes of data. With the right technology solutions, these companies can move beyond traditional real-time monitoring to more agile real-time prediction. By rapidly analyzing incoming technical and business data—and applying that information to complex models in real time—they can generate tactical insights that help increase drilling and production performance while preventing problems. By quickly searching and analyzing a large volume and variety of competitive intelligence, such as news about competitive mergers, acquisitions or new investments, they can substantially improve strategic decision making.
Using IBM Security Intelligence with Big Data, security organizations can analyze more data more flexibly, and gain more accurate results. By analyzing structured, enriched security data alongside unstructured data from across the enterprise, the IBM solution helps find malicious activity hidden deep in the masses of an organization’s data, for advanced threat and risk detection.
Today, two major factors are poised to change the insurance industry in a way it hasn’t seen in more than 50 years—emerging capabilities enabled by cognitive computing and big data, and an empowered consumer. We are starting to get a glimpse of the possibilities these trends hold, as well as the challenges they represent. To understand their full impact on the future of the insurance industry, we need to look at the past to understand how paradigm shifts in the insurance industry follow paradigm shifts in the underlying computing technology. If history is any indication, these technologies will usher in a new paradigm for the insurance industry.
Harness the Power of Big Data is the latest book by several authors of Understanding Big Data, the hugely popular book that debuted in 2011. Big data represents a new era of computing – an inflection point of opportunity where data in any format may be explored and utilized for breakthrough insights - whether that data is in-place, in-motion, or at-rest.
Harness the Power of Big Data includes a chapter titled "If Data Is the New Oil—You Need Data Exploration and Discovery." This chapter covers many of the key benefits of IBM InfoSphere Data Explorer, a new product in the IBM big data portfolio that enables users to access all of the data that they need in a single integrated view, regardless of its format, how it’s managed, or where it’s stored. Being able to retrieve data from all available repositories in an organization is a key part of doing analysis involving Big Data, especially for exploratory analysis.
Authors: Paul Zikopoulos, Dirk Deroos, Krishnan Parasuraman, Thomas Deutsch, David Corrigan, James Giles
Rising costs, chronic illness, an aging population and a shortage of professionals are forcing massive changes in the healthcare industry. To gain insight into how they can improve service while reducing costs, healthcare payers and providers are turning to data and analytics. Leading organizations are treating data as a strategic asset and putting processes and systems in place that help healthcare professionals improve decision-making and drive actionable results.
This paper discusses the value that data and analytics provide, and gives examples of organizations that are already leveraging a wide range of big data capabilities to deliver clinical and financial benefits. Readers will learn the steps that organizations should take to become data-driven and the capabilities that IBM provides to help them improve business outcomes.