The synergy between predictive analytics and decision optimization is critical to good decision making. Predictive analytics offers insights into likely future scenarios, and decision optimization prescribes best-action recommendations for how to respond to those scenarios given your business goals, business dynamics, and potential tradeoffs or consequences.
Together, predictive analytics and decision optimization provide organizations with the ability to turn insight into action—and action into positive outcomes.
In this white paper, you’ll gain a better understanding of:
The difference between predictive and prescriptive analytics
How predictive and prescriptive actions complement one another to help you achieve optimized business decisions
IBM’s approach to creating a powerful end-to-end decision management system
Many companies can't predict which customer they will retain or which customers will increase their spend. With predictive analytics they can.
This knowledge brief from Aberdeeon Group highlights research findings that show organizations which apply predictive analytics are able to:
Establish timely and accurate insights into customer behavior.
Empower employees to do their jobs more effectively.
Encourage more repeat business and higher wallet share
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.
Hear Masood Heydari, SVP of SPARC Engineering, discuss details of Oracle's servers designed for cloud and scale-out, which provide security by default, better core efficiency for cloud apps, and accelerate data analytics at X86 commodity cost points
Learn how to create cloud infrastructure that's secure by default and has better core efficiency for Java, database, and big data. Oracle's servers offer hardware acceleration of data analytics and machine learning, with 10X better time-to-insight.
"With the introduction of Oracle Database In-Memory and servers with the SPARC S7 and SPARC M7 processors Oracle delivers an architecture where analytics are run on live operational databases and not on data subsets in data warehouses. Decision-making is much faster and more accurate because the data is not a stale subset. And for those moving enterprise applications to the cloud, Real-time analytics of the SPARC S7 and SPARC M7 processors are available both in a private cloud on SPARC servers or in Oracle’s Public cloud in the SPARC cloud compute service.
Moving to the Oracle Public Cloud does not compromise the benefits of SPARC solutions. Some examples of utilizing real time data for business decisions include: analysis of supply chain data for order fulfillment and supply optimization, analysis of customer purchase history for real time recommendations to customers using online purchasing systems, etc.
According to Mary Johnston Turner, Research Vice President at IDC; "Breaking down technology specific management as well as data silos also facilitates faster infrastructure and application rollouts, reduces human errors, and improves overall business agility.Cloud based management, monitoring and analytics help to improve collaboration between IT operations and developer teams by stabilizing service levels and monitoring usage to support accurate charge back."
Mobile is the new normal for users to connect and consume content, you need to consider apps, mobile integration,security, analytics, development tools, life-cycle management, various mobile stakeholders, and the overall enterprise mobile ecosystem.
This report explores the evolution of the key features of course apps mobility, interactivity, engaging design, and integrated analytics — and showcase how course apps are sparking new thinking in higher education about the next iteration of digital learning resources.
Le rapport note cependant que les investissements dans l’analytics sont en perte de vitesse. Apparemment, les entreprises ont tellement à cœur de se prêter au jeu de l’expérience qu’elles ont tendance à s’éparpiller, quitte à négliger l’essentiel.
Java applications have been a central technology for enterprises for two decades. This wealth of data, functionality, and knowledge are critical to enterprises. With Java-based applications, modern development can build on a platform that enables cloud-native architectures while simultaneously supporting existing applications. This combination of traditional enterprise-wide monoliths and cloud-based application deployment allows organizations to take advantage of existing knowledge and resources while actively moving toward newer application models.
Making key decisions that improve business performance requires more than simple insights. It takes deep data discovery and a keen problem solving approach to think beyond the obvious. As a business leader, you ought to have access to information most relevant to you that helps you anticipate potential business headwinds and craft strategies which can turn challenges into opportunities finally leading to favorable business outcomes.
WNS DecisionPoint , a one-of-its kind thought leadership platform tracks industry segments served by WNS and presents thought-provoking original perspectives based on rigorous data analysis and custom research studies. Coupling empirical data analysis with practical ideas around the application of analytics, disruptive technologies, next-gen customer experience, process
transformation and business model innovation; we aim to arm you with decision support frameworks based on points of fact.
Data is growing at amazing rates and will continue this rapid rate of growth. New techniques in data processing and analytics including AI, machine and deep learning allow specially designed applications to not only analyze data but learn from the analysis and make predictions.
Computer systems consisting of multi-core CPUs or GPUs using parallel processing and extremely fast networks are required to process the data. However, legacy storage solutions are based on architectures that are decades old, un-scalable and not well suited for the massive concurrency required by machine learning. Legacy storage is becoming a bottleneck in processing big data and a new storage technology is needed to meet data analytics performance needs.
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-fl ash storage infrastructure that is built specifically to work with high-powered analytics.
Everybody’s talking about big data. Huge promises have been made about its role in driving enterprises forward. But few organizations are realizing its true benefits.
For those able to put data to good use, there’s much to be excited about. Data is transforming not only businesses, but entire industries, and the world as we know it. Today organizations are harnessing big data to do things like transform healthcare, provide eyesight for the visually impaired, and bringing us closer to autonomous cars
Apache Spark has become a critical tool for all types of businesses across all industries. It is enabling organizations to leverage the power of analytics to drive innovation and create new business models.
The availability of public cloud services, particularly Amazon Web Services, has been an important factor in fueling the growth of Spark. However, IT organizations and Spark users are beginning to run up against limitations in relying on the public cloud—namely control, cost and performance.
Hewlett-Packard (HP) is unique in this EMA Radar in its ability to combine two threads – a single analytic overlay as embodied in its Service Health Analyzer (SHA) product, and a broader suite solution optimized for HP to participate in all three use cases here with maximum functional impact. This is not entirely a black-and-white situation, as SHA does leverage and currently largely depends on integration with HP Business Service Management 9.1, which is itself a suite. But SHA can assimilate other third-party sources, checks out brilliantly in early-phase deployments in terms of time-to-value and analytic power, and is the lead reason for HP’s strong Value Leader showing in technical performance management.
Do your leaders have what it takes to generate improved performance and execution from their employees. Get your report now, compliments of SuccessFactors, and ensure that your business has the leadership capital it needs.
With today's shortage of critical talent, strategic workforce planning is one of HR's most important responsibilities. Discover the common pitfalls that trap many companies-and how to avoid them. Get your compliments report from SuccessFactors now.
These days, a company success depends on whether it hired the right people to effectively execute its strategies. Download this paper, compliments of SuccessFactors, and learn the critical questions you should ask before interviewing talent.
Will the people you need for your future workforce be there? This complimentary SuccessFactors white paper shows how to shorten the journey to data-driven decision-making about talent. Download it today.
Technology plays an integral role in enabling businesses to have access to insightful analytics. By providing metrics on core workforce facts, workforce financials, productivity and performance, talent development and succession and human capital risk, companies are able to identify those 10- 15 metrics most important to business goals. This will enable them to present the Board of Directors with a comprehensive and concise story of workforce capabilities. The best place, we suggest, is with expert, practical guidance. Download this informative resource.
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.