Published By: IBM
Published Date: Oct 03, 2017
Every day, torrents of data inundate IT organizations and overwhelm
the business managers who must sift through it all to
glean insights that help them grow revenues and optimize
profits. Yet, after investing hundreds of millions of dollars into
new enterprise resource planning (ERP), customer relationship
management (CRM), master data management systems (MDM),
business intelligence (BI) data warehousing systems or big data
environments, many companies are still plagued with disconnected,
“dysfunctional” data—a massive, expensive sprawl of
disparate silos and unconnected, redundant systems that fail to
deliver the desired single view of the business.
| |
|
|
|
Published By: IBM
Published Date: Oct 03, 2017
Many new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data.
To keep pace with regulatory changes, many banks will need to reapportion their budgets to support the development of new systems and processes. Regulators continually indicate that the banks must be able to provide, secure and deliver high-quality information that is consistent and mature.
| |
|
|
|
|
|
|
|
Published By: Sybase
Published Date: May 10, 2012
This white paper, based on a survey of database professionals, examines the problems facing many large businesses that are attempting to remain agile while dealing with a mountain of data under management.
| |
|
|
|
Published By: Sybase
Published Date: May 10, 2012
Sybase's Adaptive Server® Enterprise (ASE) is a high performance relational database management system for mission-critical, data intensive environments that has been meeting these needs for nearly three decades.
| |
|
|
|
Published By: Sybase
Published Date: May 10, 2012
Download this white paper for analysis of survey results that compare TCO of Sybase ASE compared to Oracle.
| |
|
|
|
Published By: Sybase
Published Date: May 10, 2012
This webcast discusses the technical benefits of Sybase ASE's compression technology. Watch the recording to learn more and to hear about use cases, strategies for data migration and a look at the performance implications.
| |
|
|
|
|
|
|
|
|
|
Published By: InMage
Published Date: Feb 24, 2009
This paper describes a series of tests run to determine the viability of continuous data protection (CDP) using InMage DR Scout along with Agami Systems AIS 3000 series of unified storage systems.
| |
|
|
|
|
|
|
|
|
|
Published By: IBM
Published Date: Jun 22, 2010
Learn how IBM's DB2 portfolio can help transform your data center. Download this free white paper from IBM to learn more!
| |
|
|
|
Published By: IBM
Published Date: Jun 22, 2010
Download this free IBM white paper to learn how to better manage your data center with System z.
| |
|
|
|
Published By: SAS
Published Date: Aug 28, 2018
Starting data governance initiatives can seem a bit daunting. You’re establishing strategies and policies for data assets. And, you’re committing the organization to treat data as a corporate asset, on par with its buildings, its supply chain, its employees or its intellectual property.
However, as Jill Dyché and Evan Levy have noted, data governance is a combination of strategy and execution. It’s an approach that requires one to be both holistic and pragmatic:
• Holistic. All aspects of data usage and maintenance are taken into account in establishing
the vision.
• Pragmatic. Political challenges and cross-departmental struggles are part of the
equation. So, the tactical deployment must be delivered in phases to provide quick
“wins” and avert organizational fatigue from a larger, more monolithic exercise.
To accomplish this, data governance must touch all internal and external IT systems and establish decision-making mechanisms that transcend organizational silos. And, it must provi
| |
|
|
|
Published By: SAS
Published Date: Jan 04, 2019
How can you open your analytics program to all
types of programming languages and all levels of
users? And how can you ensure consistency across
your models and your resulting actions no matter
where they initiate in the company?
With today’s analytics technologies, the conversation
about open analytics and commerical analytics is no
longer an either/or discussion. You can now combine
the benefits of SAS and open source analytics
technology systems within your organization.
As we think about the entire analytics life cycle, it’s
important to consider data preparation, deployment,
performance, scalability and governance, in addition
to algorithms. Within that cycle, there’s a role for
open source and commercial analytics.
For example, machine learning algorithms can
be developed in SAS or Python, then deployed in
real-time data streams within SAS Event Stream
Processing, while also integrating with open systems
through Java and C APIs, RESTful web services,
Apache Kafka, HDFS and more.
| |
|
|
|
Published By: SAS
Published Date: Jan 04, 2019
As the pace of business continues to accelerate, forward-looking organizations are beginning to
realize that it is not enough to analyze their data; they must also take action on it. To do this, more
businesses are beginning to systematically operationalize their analytics as part of a business process.
Operationalizing and embedding analytics is about integrating actionable insights into systems and
business processes used to make decisions. These systems might be automated or provide manual,
actionable insights. Analytics are currently being embedded into dashboards, applications, devices,
systems, and databases. Examples run from simple to complex and organizations are at different
stages of operational deployment. Newer examples of operational analytics include support for
logistics, customer call centers, fraud detection, and recommendation engines to name just a few.
Embedding analytics is certainly not new but has been gaining more attention recently as data
volumes and the freq
| |
|
|
|
Published By: IBM
Published Date: Apr 04, 2013
Business users need a simple but powerful way to navigate through data and find the insights to make timely, critical business decisions. Unfortunately, many users have become frustrated at their inability to quickly access and analyze the
information they require. This data typically includes a combination of personal and corporate data locked in various enterprise systems. It exists in different formats and can be hard to analyze, change or share — making it difficult for people to get fast answers to business questions.
| |
|
|
|
Published By: IBM
Published Date: Apr 04, 2013
IBM PureFlex Systems combine advanced IBM hardware and software with “patterns of expertise” and integrate them into three optimized configurations that are simple to acquire and deploy. Read the data sheet to learn more about configurations optimized for small businesses, application servers, and transactional and database systems.
| |
|
|
|
Published By: Fonality
Published Date: Feb 25, 2013
A Fonality study found that for companies with knowledge workers who average an eight-hour workday, nearly 50 percent of that time-almost four hours a day.
| |
|
|
|
Published By: IBM
Published Date: Sep 27, 2013
IBM PureFlex Systems combine advanced IBM hardware and software with “patterns of expertise” and integrate them into three optimized configurations that are simple to acquire and deploy. Read the data sheet to learn more about configurations optimized for small businesses, application servers, and transactional and database systems.
| |
|
|
|
Published By: IBM
Published Date: Sep 27, 2013
Business users need a simple but powerful way to navigate through data and find the insights to make timely, critical business decisions. Unfortunately, many users have become frustrated at their inability to quickly access and analyze the information they require. This data typically includes a combination of personal and corporate data locked in various enterprise systems. It exists in different formats and can be hard to analyze, change or share — making it difficult for people to get fast answers to business questions.
| |
|
|
|
|
 |
|
|
|
|