Published By: IBM APAC
Published Date: Jun 07, 2017
The analytics tools you’ve come to rely on probably haven’t kept pace with this rapid change, and may now be less effective. Systems may not be nimble enough to follow customer journeys across channels and time. Different platforms in different departments can’t talk to each other, so reporting is slowed. And it’s difficult to take proactive steps when your view of the total customer experience is a little blurry.
Download this white paper to find out more.
Predictive analytics is powerful. It can help drive significant improvement to an organization’s bottom line. Look for ways to use it to grow revenue, shrink costs and improve margins.
Provide a platform that enables your data scientists to work efficiently using tools and algorithms they prefer. Enhance your analyses with internal and external data, structured and unstructured data. Then make the analytics accessible in order to reap the full benefits of these valuable analyses.
Stay ahead of the curve in your market with predictive analytics, and give your organization a competitive advantage and an improved bottom line.
NoSQL databases and Apache Spark are a potent combination for rapid
integration, transformation and analysis of all kinds of business data.
With its data syncing and analytics capabilities, IBM Cloudant offers unique
advantages as a NoSQL database for many Spark use cases.
IT decision-makers, data scientists and developers need to know how and when to
apply these technologies most effectively.
IBM can offer a host of resources and tools to help your organization gain value
from Cloudant and Spark quickly, and with minimal up-front investment.
With more data in the hands of more people – and easier access to easy-to-use analytics – conversations about data and results from data analysis are happening more often. And becoming more important. And expected. So it’s not surprising that improved collaboration is one of the most common organizational goals.
Let’s take a look at how you can use results produced by SAS Visual Analytics with Microsoft Office applications. You’ll see how easy it is to combine sophisticated analytic visualizations and reports with Microsoft’s widely used productivity tools – to share insights, improve collaboration and drive increased adoption of analytics and BI across your organization.
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.
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.
Published By: Pentaho
Published Date: Nov 04, 2015
This report explains the benefits that Hadoop and Hadoop-based products can bring to organizations today, both for big data analytics and as complements to existing BI and data warehousing technologies based on TDWI research plus survey responses from 325 data management professionals across 13 industries. It also covers Hadoop best practices and provides an overview of tools and platforms that integrate with Hadoop.
Published By: LogMeIn
Published Date: Mar 19, 2015
Remote support technology, including remote control, desktop sharing, and web collaboration, is one of the most popular platforms used across TSIA service disciplines. Today’s remote support solutions offer much more than just remote control for PCs, their functional footprint is expanding to include support for more devices and richer analytics for trend analysis and supervisor dashboards. Remote support solutions are typically well regarded by users, consistently delivering one of the highest average satisfaction scores in TSIA’s annual Global Technology Survey. Service executives should acquaint themselves with the new features and capabilities being introduced by leading remote support platforms and find ways to leverage the capabilities beyond technical support. Field services, education services, professional services, and managed services are all increasing adoption of these tools to boost productivity and avoid on-site visits. Download this white paper to learn more.
This paper is divided into two parts. The first part provides some background and a comparison of the types of episode analytics. Part two explores the real-world experiences of payers and providers in using episode analytics for payment bundling and other purposes.
Finally, we offer some recommendations on how to use episode analytics to reduce variations and manage contracts that involve financial risk.
Read more to learn how Cisco’s Mobile Experience Business Offer can unleash the power of your network to better serve your customers with locations based analytics, real time interactions, and mobile experience development tools.
Published By: Red Hat
Published Date: Jun 23, 2016
FICO, a data analytics software company, wanted to diversify into new markets its core offering of providing on-premise software to major corporations. To do this, the company launched FICO Analytic Cloud, a cloud delivery channel that enables FICO to serve organizations of all sizes. FICO Analytic Cloud was first launched in 2013 and provides Platform-as-a-Service (PaaS) access to FICO Decision Management Platform, which allows customers to use FICO tools and technology to create, customize, and deploy applications and services. FICO Decision Management Platform is built on OpenShift Enterprise by Red Hat, which provides the PaaS tools and support FICO needed to rapidly scale the platform and Analytic Cloud.