If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem.
Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.
Published By: Aberdeen
Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
Surviving and thriving amid the global, digital shopping revolution, in which consumers fluidly browse and buy from their smartphones, computers and in store, calls for a supply-chain makeover.
Pressed to offer consumers fast, flexible and even free product fulfillment and delivery in an omnichannel retail landscape, a crowdsourced, collaborative model is taking shape. Traditional roles are blurring as logistics companies, manufacturers and retailers work to meet the growing on-demand economy via the adoption of business intelligence supply chain technologies.
This paper can help you achieve successful legacy modernization projects. It presents practical steps for starting application modernization projects and describes the benefits of three high payback strategies. It also reviews the criteria for evaluating a variety of modernization tools.
The key benefit of creating a case management methodology is to multiply its effectiveness by replicating it across the organization's patient-facing departments, practices and functions. In this way, your organization can reduce costs, increase quality and streamline its operations.
Welcome to the future of 24/7, any-time, anywhere access to digital content - where dynamic publishing solutions are the mantra. Is your organization ready for this brave new world of digital content distribution? This whitepaper explores how to prime your organization to leverage rapid digital content consumption as a key to business intelligence.
They were mistaken. Research conducted by the Economist Intelligence Unit (EIU) and written in discussion with SAP shows
that many organizations are moving ahead now, some
aggressively, to integrate ML into their operations.
Location analytics is the process of
integrating geographical data into business intelligence (BI) and analytics-led decision
making. Location analytics creates meaningful insight from relationships found in
geospatial data to solve a broad variety of business and social problems.
Location data is found everywhere – with an item or a device, in a conversation or
behavior, in machines or sensors, tied to a customer or competitor, attached to a
database record or recorded from vehicles or other moving objects. Organizations
want to take advantage of location data to improve decisions, create better customer
engagement and experiences, reduce risks and automate business processes.
Business Intelligence helps retailers, warehouse staff, customer services agents, and your value chain realize new innovations, improve margins, and propel profits to new heights. Learn how Ace Hardware, Food Lion, and others leverage our software.
To better understand the benefits, costs, and risks associated with implementation of SAP Business Objects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to provide the conclusions of this cost and benefit analysis.
To better understand the benefits, costs, and risks associated with implementation of SAP BusinessObjects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to report cost and benefit findings
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit
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.
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
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.
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
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.