Digitalization—the process of exploiting digital information to maximize business success—has increased the value of your data to the point where it is arguably your most important asset. This paper explains why mastery will not be possible with merely adequate integration technology.
The ability to deploy Hadoop clusters in the public cloud, on premises or in appliance form should be a critical requirement for your Hadoop distribution selection. And rolling out Hadoop clusters on both the Linux and Windows operating systems will be another important criterion for a great many enterprise customers. Register now to learn about all of this in a single webinar.
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.
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.
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.
Leading companies and technology providers are rethinking the fundamental model of analytics, and the contours of a new paradigm are emerging. The new generation of analytics goes beyond Big Data (information that is too large and complex to manipulate without robust software), and the traditional narrow approach of analytics which was restricted to analysing customer and financial data collected from their interactions on social media. Today companies are embracing the social revolution, using real-time technologies to unlock deep insights about customers and others and enable better-informed decisions and richer collaboration in real-time.
In a contact center environment, real-time analytics provide the live information needed to respond to difficult situations before a customer, a sale, or an opportunity is lost. Scott Bakken and David Patchen from MainTrax and Brandon Rowe from Interactive Intelligence discuss how real-time analytics help your business operate at optimal levels and experience increased growth and reduced costs.
For many enterprises System z is central to modern analytics because of the vast quantities or rich data stored upon it – not to mention excellent qualities of service. Carl Olofson, an IDC analyst looks, at the role of the mainframe in relation to big data, how it has become a hub for modern day analytics, its ability to integrate information from other sources to enhance business decisions and how it is positioned for the future. Download this paper and learn.
Discover new opportunities for maturing your data practices—and building your business results. You’ll learn how to move beyond mere web analytics to build a more comprehensive marketing analytics approach that includes mobile, social, and offline channels. And you’ll see how your current analytics capabilities compare to those of similar organizations and where you have opportunities for improvement.
The solution to operationalizing analytic s involves the effective combination of a Decision Management approach with a robust, modern analytic technology platform. This paper discusses both how to use a focus on decisions to ensure the right problem gets solved and what such an analytic technology platform looks like.