Whether your company has been selling online for 20 minutes or 20 years, you are
undoubtedly familiar with the PCI DSS (Payment Card Industry Data Security Standard). It
requires merchants to create security management policies and procedures for safeguarding
customers’ payment data.
Originally created by Visa, MasterCard, Discover, and American Express in 2004, the PCI DSS
has evolved over the years to ensure online sellers have the systems and processes in place
to prevent a data breach.
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.
Published By: Lookout
Published Date: Apr 18, 2018
The world has changed. Yesterday everyone had a managed PC for work and all enterprise data was behind a firewall. Today, mobile devices are the control panel for our personal and professional lives. This change has contributed to the single largest technology-driven lifestyle change of the last 10 years.
As productivity tools, mobile devices now access significantly more data than in years past. This has made mobile the new frontier for a wide spectrum of risk that includes cyber attacks, a range of malware families, non-compliant apps that leak data, and vulnerabilities in device operating systems or apps. A secure digital business ecosystem demands technologies that enable organizations to continuously monitor for threats and provide enterprise-wide visibility into threat intelligence.
Watch the webinar to learn more about:
What makes up the full spectrum of mobile risks
Lookout's Mobile Risk Matrix covering the key components of risk
How to evolve beyond mobile device management
This spotlight report examines:
• How Manufacturing Operations Management (MOM) or Manufacturing Execution Systems (MES) are key enablers of data management and Digital Transformation. Companies can combine many other opportunities with manufacturing operations in a digital journey.
• Product lifecycle management (PLM) as a high-value discipline to pair with MOM in discrete manufacturing, and the value of digital continuity across engineering, manufacturing operations, and supply chain.
• A robust integration of MOM and PLM technologies and the advent of the Digital Twin (a virtual copy of the product and how it's made) to demonstrate maturity in Smart Manufacturing and the ability to make smart products in smart factories.
The IIoT has opened up a world of opportunity for manufacturers. Take advantage of it.
Published By: Datastax
Published Date: Nov 02, 2018
Most enterprises operate in a hybrid cloud environment, whether they know it or not. The benefits of hybrid cloud and multi-cloud architectures are numerous, but since most companies don’t even realize they’re using multi-cloud, they’re not taking full advantage of the multi/hybrid cloud environment. Read this ebook to learn how proper data management via an enterprise data layer empowers enterprises to unlock the full potential of their multi- and/or hybrid cloud strategies to achieve data autonomy while scaling efficiently, effectively, and safely.
The EU General Data Protection Regulation (GDPR) has arrived. Every company doing business with
European customers — regardless of location — must make considerable governance, people, process,
and technology changes to comply with the new rules. While companies have made progress, more work
remains. To succeed, they must tackle key challenges, including data identification, mapping, and access
management. Despite the work ahead, forward-looking businesses understand GDPR is an opportunity.
This is a transformation for a data-savvy world, with the potential to yield enhanced customer and
business benefits. Investment in solutions with data privacy, security, and compliance offerings that can
protect data no matter where it’s stored — on-premises and in the cloud — can ease companies along
their readiness journeys and help them achieve and sustain compliance from May 25, 2018, and onward
Sage Business Cloud Enterprise Management offers you a comprehensive, real-time solution that delivers accurate, up-to-date data that identifies and mitigates the consequences of product recalls and other supply chain issues.
With Sage Business Cloud Enterprise Management, your food and beverage business will have a faster, simpler and flexible way to keep the costs and reputational damage of recalls to a minimum.
Published By: Panduit
Published Date: Aug 28, 2018
Interested in learning how the right physical and network infrastructure approach in your colocation data center facility can help you stabilize costs, provide better security, and help promote growth for you and your tenants? Download the Panduit white paper Optimizing Colocation Infrastructure Strategies to learn how to overcome the challenges of aging colocation data center infrastructure and onboard new tenants quickly.
Published By: Panduit
Published Date: Oct 09, 2018
Interested in learning how to stabilize costs and promote growth for you and your tenants? Download the Panduit white paper Colocation Provider Strategies for Success to learn how you can enable ongoing monitoring and maximize your colo data center’s efficiency.
Published By: StreamSets
Published Date: Sep 24, 2018
The advent of Apache Hadoop™ has led many organizations to replatform their existing architectures to reduce data management costs and find new ways to unlock the value of their data. One area that benefits from replatforming is the data warehouse. According to research firm Gartner, “starting in 2018, data warehouse managers will benefit from hybrid architectures that eliminate data silos by blending current best practices with ‘big data’ and other emerging technology types.” There’s undoubtedly a lot to ain by modernizing data warehouse architectures to leverage new technologies, however the replatforming process itself can be harder than it would at first appear. Hadoop projects are often taking longer than they need to create the promised benefits, and often times problems can be avoided if you know what to avoid from the onset.
Consumers worldwide continue to adopt and use technology in their shopping experience.
Faced with rising customer expectations and increasing competitive pressures, retailers
now are prioritizing in-store innovation. Many retailers have adopted multichannel
implementations, in which mobile, web, and in-store shopping are enabled but not delivered
consistently to the customer. The next step in this evolution is an omnichannel strategy, now
being deployed by some retailers, which presents a consistent shopping experience across
mobile, web, and in-store channels. Omnichannel also enables retailers to integrate back-end
infrastructure technologies (e.g., servers, databases, etc.) and cloud-based services (e.g., loyalty
programs, personalized recommendations, inventory management, etc.) to improve many
aspects of store and enterprise operations.
An omnichannel strategy relies on several core and supporting technologies. The key factors in
evaluating any omnichannel-enabling solution includ
Improved business productivity often requires more efficient IT and more efficient IT cannot be achieved without a better understanding of the way business services are run and delivered. Configuration Management Databases (CMDBs) have emerged as a central component for Information Technology Infrastructure Library (ITIL) and business service management (BSM).
Today’s organisations are tasked with analysing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organisations are finding that in order to deliver analytic insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store enormous amounts of data in a central location, so it’s readily available to be categorised, processed, analysed, and consumed by diverse groups within an organisation? Since data—structured and unstructured—can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
Today AMP Ltd. integrates and manages its customer data more efficiently using a single Talend platform that enables data reconciliation, quality-assessment dashboards, and metadata management. Ten billion rows of AMP Ltd. data are computed in less than an hour.
In this webinar you will learn how you can modernize your data architecture to help you collect and validate data, act upon it, and transform your organization for the digital age.
Published By: Extensis
Published Date: Jun 08, 2010
Metadata Management is the process of ensuring that all metadata associated with a digital asset is captured, organized, stored and made available for use by and within other applications. Metadata Management begins at the moment the digital asset is created by an application or captured by digital imaging.
You may know some data management basics, but are you aware of the transformational results that can result from doing data management right? This paper explains core data management capabilities, then describes how a solid data management foundation can help you get more out of your data.
Fraudsters are only becoming smarter. How is your organization keeping pace and staying ahead of fraud schemes and regulatory mandates to monitor for them? In this e-book, learn the basics in how to prevent fraud, achieve compliance and preserve security.
Despite heavy, long-term investments in data management, data problems at many organizations continue to grow. One reason is that data has traditionally been perceived as just one aspect of a technology project; it has not been treated as a corporate asset. Consequently, the belief was that traditional application and database planning efforts were sufficient to address ongoing data issues.
As our corporate data stores have grown in both size and subject area diversity, it has become clear that a strategy to address data is necessary. Yet some still struggle with the idea that corporate data needs a comprehensive strategy.
There’s no shortage of blue-sky thinking when it comes to organizations’ strategic plans and road maps. To many, such efforts are just a novelty. Indeed, organizations’ strategic plans often generate very few tangible results for organizations – only lots of meetings and documentation. A successful plan, on the other hand, will identify realistic goals along with a r
Data integration (DI) may be an old technology, but it is far from extinct. Today, rather than being done on a batch basis with internal data, DI has evolved to a point where it needs to be implicit in everyday business operations. Big data – of many types, and from vast sources like the Internet of Things – joins with the rapid growth of emerging technologies to extend beyond the reach of traditional data management software. To stay relevant, data integration needs to work with both indigenous and exogenous sources while operating at different latencies, from real time to streaming. This paper examines how data integration has gotten to this point, how it’s continuing to evolve and how SAS can help organizations keep their approach to DI current.
Machine learning systems don’t just extract insights from the data they are fed, as traditional analytics do. They actually change the underlying algorithm based on what they learn from the data. So the “garbage in, garbage out” truism that applies to all analytic pursuits is truer than ever.
Few companies are already using AI, but 72 percent of business leaders responding to a PWC survey say it will be fundamental in the future. Now is the time for executives, particularly the chief data officer, to decide on data management strategy, technology and best practices that will be essential for continued success.
You may know some basics about data management, but do you realize the transformational results data-management-done-right can produce? This paper explains core data management capabilities, then describes how a solid data management foundation can help you get more out of your data. From getting fast, easy access to trustworthy data to making better decisions and becoming a data-driven business, you’ll learn why good data management is essential to success. Multiple real-world examples illustrate how SAS customers have used data management to improve customer experience, boost revenue, remain compliant and become more efficient.
“Unpolluted” data is core to a successful business – particularly one that relies on analytics to survive. But preparing data for analytics is full of challenges. By some reports, most data scientists spend 50 to 80 percent of their model development time on data preparation tasks. SAS adheres to five data management best practices that help you access, cleanse, transform and shape your raw data for any analytic purpose. With a trusted data quality foundation and analytics-ready data, you can gain deeper insights, embed that knowledge into models, share new discoveries and automate decision-making processes to build a data-driven business.
With the amount of information in the digital universe doubling every two years, big data governance issues will continue to inflate. This backdrop calls for organizations to ramp up efforts to establish a broad data governance program that formulates, monitors and enforces policies related to big data. Find out how a comprehensive platform from SAS supports multiple facets of big data governance, management and analytics in this white paper by Sunil Soares of Information Asset.
Risks have intensified as retailers and financial organizations embrace new technologies to meet customer demands for convenience. The rise of mobile and online transactions introduces new risks – and with that, new requirements for fraud mitigation. This paper discusses key steps for fighting back against fraud risk by establishing appropriate and accurate data, analytics and alert management.
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