As recognized leader in master data management (MDM), and a pioneer in data asset management, TIBCO EBX™ software is an innovative, single solution for managing, governing, and consuming all your shared data assets. It includes all the enterprise class capabilities you need to create data management applications including user interfaces for authoring and data stewardship, workflow, hierarchy management, and data integration tools. And it provides an accurate, trusted view of business functions, insights, and decisions to empower better decisions and faster, smarter actions.
Download this datasheet to learn:
What makes EBX™ software unique
Various capabilities of EBX software
The data it manages
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.
Cloud services are a pillar of a digital transformation,
but they have also become a thorn in the side of many
security architects. As data and applications that were
once behind the enterprise firewall began roaming
free—on smartphones, between Internet-of-Things
(IoT) devices, and in the cloud—the threat landscape
expanded rapidly. Security architects scrambled to adjust
their technologies, policies, and procedures. But just
when they thought they had a handle on securing their
cloud-connected enterprises, new business imperatives
indicated that one cloud wasn’t enough.
Modern enterprises operate in a multi-cloud world,
where the threat landscape has reached a new level of
complexity. Security teams are juggling a hodgepodge
of policies, threat reports, and management tools. When
each cloud operates in its own silo, the security architect
has even more difficulty supporting the CISO or CIO with a
coherent, defensible security posture.
Published By: Dell EMC
Published Date: Oct 08, 2015
Download this whitepaper to learn more about how to capture, analyze and manage a tidal wave of structured and unstructured data, turn this data into operational intelligence, And how to overcome the limitations of databases and data management tools that weren’t designed for a world of big data with Dell.
Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes.
This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.
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.
The advent of cloud computing and software-defined data center architectures for modern application delivery has made networking more sensitive than ever before. Applications in the digital age require networks that can expand and contract dynamically based on consumer demand. Enterprises are implementing software-defined networking (SDN) to deliver the automation required by these new environments, but the dynamic nature of SDN makes network management and monitoring fundamentally more challenging.
Network infrastructure teams need monitoring tools that can provide visibility into these new and constantly changing networks. This white paper explores the importance of SDN monitoring and examines a leading example of a solution, CA Performance Management with CA Virtual Network Assurance integration.
Data-driven asset performance management can help food & beverage manufacturers leverage tools such as equipment efficiency solutions, augmented reality and secure asset connection to transition from a reactive to a prescriptive approach. This will not only help reduce CapEx and OpEx, but also empower the workforce, whilst meeting manufacturing KPIs.
This report from Frost & Sullivan shows how manufacturers can achieve 20-30% cost savings by changing their asset maintenance approach.
Published By: Lookout
Published Date: Aug 30, 2017
Mobility is exploding. Workers and businesses fully
expect to work anywhere, any time, from any device.
Riding right alongside this growth is the amount of data
created and consumed on mobile devices. While this
presents organizations with an attractive means of
empowering flexibility and productivity, the security risks
are real and daunting.
Unfortunately, while enterprise mobility management
tools can provide valuable administrative capabilities
and protect the organization from phone loss, accidental
data loss or weak passwords, they lack the necessary
visibility into today’s modern security risks, including
malware and other device-centric attacks
Product Lifecycle Management (PLM) software can help your company keep up with the increasing complexity of developing today’s high-tech products. While smaller companies may use relatively simple Product Data Management (PDM) tools, larger companies rely on full-featured PLM systems that help automate processes and share data across global supply chains. Mid-size companies can feel stuck because PDM is too basic, but PLM feels out of reach.
This resource will help you:
• Recognize why “simple” solutions fall short and do not support your capabilities
• Better connect to customers and the supply chain
• Drive higher product development speed
• Get started with the right PLM solution
Midsize manufacturers need a system that quickly delivers the core capabilities they need to streamline product development but also gives them room to grow value over time. So, what’s the right size PLM to fit a midsized high-tech company? Download this resource and take a look.