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information processing

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By: CheckMarx     Published Date: Sep 12, 2019
Financial services organizations operate under a host of regulatory standards. This makes sense, as the assets and information managed by these firms are valuable, sensitive, and targeted by sophisticated cyber attackers daily. Compounding these challenges is the large volume of personally identifiable information (PII) that financial organizations handle regularly. PII is subject to many compliance regulations, notably the General Data Protection Regulation (GDPR), which regulates not only the processing of personal data, including PII, relating to individuals in the EU, for also any organization that processes personal data of EU residents. For US banking consumers, Section 5 (Unfair or Deceptive Acts or Practices) of the Federal Trade Commission Act and numerous state regulations enforce basic consumer protections, which financial organizations must also uphold.
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     CheckMarx
By: Medius     Published Date: Oct 01, 2019
Marc Jacobs has been able to redirect employees from the considerable time spent maintaining spreadsheets and managing AP information. In just four months after deploying MediusFlow, the company was able to justify the investment. One year from deployment, it expects to have made $150,000 in productivity gains. By modernizing its solution for invoice processing, Marc Jacobs can easily manage its complex supply chain and get back to the creative work of designing and delivering next season’s collection.
Tags : ap automation, invoice processing, invoice automation, accounts payable automation, accounting software, accounting automation, microsoft dynamics automation
     Medius
By: SAP     Published Date: Feb 03, 2017
The spatial analytics features of the SAP HANA platform can help you supercharge your business with location-specific data. By analyzing geospatial information, much of which is already present in your enterprise data, SAP HANA helps you pinpoint events, resolve boundaries locate customers and visualize routing. Spatial processing functionality is standard with your full-use SAP HANA licenses.
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     SAP
By: Cisco EMEA     Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
Tags : big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
     Cisco EMEA
By: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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     Oracle CX
By: Infosys     Published Date: May 30, 2018
Customers today are far more concerned about the contents and origin of a product than ever before. in such a scenario, granting them easy access to product information, via digital initiatives such as SmartLabel™, goes a long way in strengthening customer trust in a brand. But it also means expending several man-hours of effort processing unstructured data, with the possibility of human error. Intelligent automation can help save effort and time, with virtually error-free results. A consumer products conglomerate wanted a smart solution to implement SmartLabel™ compliance. See how Infosys helped and the five key takeaways from the project.
Tags : automation, brand, information, digital, customer
     Infosys
By: Red Hat     Published Date: May 11, 2016
Platform-as-a-Service (PaaS) provides an abstraction that makes developers more productive by helping them focus on creating applications rather than dealing with infrastructures. This is important as information and its associated processing has become central to more businesses, even those in industries that haven’t been historically thought of as dependent on information technology. And that makes writing custom applications in support of an organization’s business objectives more important than ever.
Tags : red hat, paas, platform, developer
     Red Hat
By: Netsuite DWASF Leads Display Q1 2015     Published Date: Feb 03, 2015
A step-change in the pace of business today brings enterprise resource planning (ERP) systems face-to-face with the largest transformation in their role since they were first introduced in the early 1990s. The rise of a new generation of business automation demands real-time information processing and visibility on a scale that was unthinkable just a few years ago. Coupled with—and in large part enabled by—this new wave of business automation, there has been a surge in the pace of business itself. Learn how Real-Time ERP puts you and your business at the forefront of this change.
Tags : real-time erp, enterprise, business automation demands, information processing and visibility
     Netsuite DWASF Leads Display Q1 2015
By: Intel     Published Date: Feb 28, 2019
Keeping the lights on in a manufacturing environment remains top priority for industrial companies. All too often, factories are in a reactive mode, relying on manual inspections that risk downtime because they don’t usually reveal actionable problem data. Find out how the Nexcom Predictive Diagnostic Maintenance (PDM) system enables uninterrupted production during outages by monitoring each unit in the Diesel Uninterrupted Power Supplies (DUPS) system noninvasively. • Using vibration analysis, the system can detect 85% of power supply problems before they do damage or cause failure • Information processing for machine diagnostics is done at the edge, providing real-time alerts on potential issues with ample of lead time for managers to rectify • Graphic user interface offers visual representation and analysis of historical and trending data that is easily consumable
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     Intel
By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
As organizations develop next-generation applications for the digital era, many are using cognitive computing ushered in by IBM Watson® technology. Cognitive applications can learn and react to customer preferences, and then use that information to support capabilities such as confidence-weighted outcomes with data transparency, systematic learning and natural language processing. To make the most of these next-generation applications, you need a next-generation database. It must handle a massive volume of data while delivering high performance to support real-time analytics. At the same time, it must provide data availability for demanding applications, scalability for growth and flexibility for responding to changes.
Tags : database, applications, data availability, cognitive applications
     Group M_IBM Q1'18
By: SDL     Published Date: Sep 20, 2019
Component Content Management: A New Paradigm in Intelligent Content Services While technology has changed the world, the way that companies manage information has inherently stayed the same. The advent of near-ubiquitous connectivity among applications and machines has resulted in a data deluge that will fundamentally alter the landscape of content management. From mobile devices to intelligent machines, the volume and sophistication of data have surpassed the ability of humans to manage it with outdated methods of collection, processing, storage, and analysis. The opportunity afforded by the advent of artificial intelligence (AI) has stimulated the market to search for a better way to capture, classify, and analyze this data in its journey to digital transformation (DX). The paradigm of document-based information management has proven to be a challenge in finding, reusing, protecting, and extracting value from data in real time. Legacy systems may struggle with fragmented information
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     SDL
By: SAS     Published Date: May 24, 2018
This paper provides an introduction to deep learning, its applications and how SAS supports the creation of deep learning models. It is geared toward a data scientist and includes a step-by-step overview of how to build a deep learning model using deep learning methods developed by SAS. You’ll then be ready to experiment with these methods in SAS Visual Data Mining and Machine Learning. See page 12 for more information on how to access a free software trial. Deep learning is a type of machine learning that trains a computer to perform humanlike tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing. Deep learning is used strategically in many industries.
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     SAS
By: IBM Watson Health     Published Date: Nov 10, 2017
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
Tags : population health management, big data, data, data analytics, big data solution, data infrastructure, analytic tools, predictive modeling
     IBM Watson Health
By: Oracle     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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     Oracle
By: Epson     Published Date: Nov 20, 2017
The average organization receives 1,200 invoices every month according to the Institute of Finance & Management. What’s more, between 70 percent and 80 percent of all invoices in the United States are still paper-based. That’s a lot of information to keep track of – and a lot of paper to shuffle around. It’s no surprise, then, that 80 percent of businesses would love to streamline their accounts payable processes. But what stops them from doing so isn’t an overly complex, impossible-to understand process – it’s confusion about the unknown, and fear that automating AP will be time-consuming, difficult, and expensive. This report was developed to provide you with real, simple steps you can take to digitize and streamline your invoice processing. As you do so you’ll recognize significant benefits, including happier employees and a healthier bottom line.
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     Epson
By: Datastax     Published Date: Apr 04, 2017
As the big data ecosystem continues to expand, new technologies are addressing the requirements for managing, processing, analyzing, and storing data to help companies benefit from the rich sources of information flowing into their organizations. From NoSQL databases to open source projects to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance, and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
Tags : evolution, big data, technology, datastax, nosql
     Datastax
By: Infosys     Published Date: Jun 12, 2018
Customers today are far more concerned about the contents and origin of a product than ever before. in such a scenario, granting them easy access to product information, via digital initiatives such as SmartLabel™, goes a long way in strengthening customer trust in a brand. But it also means expending several man-hours of effort processing unstructured data, with the possibility of human error. Intelligent automation can help save effort and time, with virtually error-free results. A consumer products conglomerate wanted a smart solution to implement SmartLabel™ compliance. See how Infosys helped and the five key takeaways from the project.
Tags : automation, brand, information, digital, customer
     Infosys
By: Tidal Software     Published Date: Sep 03, 2008
Staples’ information systems play a critical role in delivering on their brand promise 'that was easy.' As part of a recent strategic imperative, Staples recently embarked on a major modernization of its systems architecture and supporting processes. The goal was to ensure IT’s systems could scale with the company’s continued global expansion without sacrificing the quality of the brand experience. One critical target for modernization was Staples’ enterprise job scheduling processes and systems. After researching the top software providers in this space, Staples selected Tidal Software to support its efforts to centralize and streamline automated batch processing.
Tags : job scheduling roi, tidal scheduler, enterprise scheduling roi, systems management tools, batch processing, systems architecture, tidal, tidal software
     Tidal Software
By: IBM     Published Date: Mar 04, 2009
The traditional view of online transactions is anchored on the idea that online stores are first and foremost a venue for transactions, which, by and large, tend to be tightly structured interactions involving the buyer and the retailer. Within this interaction, the retailer’s key job is to provide customers with the information they need to purchase–such as pricing, product descriptions and orderly merchandising–and to deliver all within the context of a superior customer experience. However, the way customers are seeking and processing this information is beginning to change, and that’s expected to have a big impact on tomorrow’s online experience.
Tags : ibm, online transactions, customer experience, online experience, moosejaw, customer satisfaction, purchasing, ecommerce
     IBM
By: Secure Computing     Published Date: Feb 06, 2008
With the recent rise in data breaches and identity thefts, implementing a sound information security program is no longer optional. Companies processing credit card information are encouraged to embrace and implement sound data protection strategies to protect the confidentiality and integrity of payment information. Some of the challenges for achieving PCI compliance are outlined in this white paper, as well as successful tips to help organizations navigate through them.
Tags : cardholder data, data security, database security, data protection, pci, pci dss, pci-dss, compliance
     Secure Computing
By: E-SignLive by Silanis     Published Date: Oct 02, 2013
While we tend to think about mobility largely as a consumer phenomenon, it is also changing how the workforce carries out business. With so much being done beyond traditional office walls, many insurance companies, financial service organizations and even government agencies are adopting mobile devices as productivity tools and developing enterprise apps for these devices. Electronic signature technology is pivotal to enabling mobile transactions beyond just informational apps. Not only in terms of straight-through processing (STP), but also for full compliance, legal enforceability and record retention. With most organizations’ mobile strategies still in the early stages, this article provides a starting point to help you better understand mobile e-signatures for business. It reviews the top 10 capabilities that businesses need in order to properly equip their customer-facing workforce with mobile e-signing.
Tags : ipad, mobility, apple, e-signatures, esign, marketing, enterprise, cio
     E-SignLive by Silanis
By: Globalscape     Published Date: Jun 27, 2014
The PCI Security Standards Council issued version 3 of their PCI DSS guidelines for processing electronic payments. Our whitepaper details the newest additions to the guidelines as well as tools and resources to help organizations comply with the standards.
Tags : globalscape, file transfer, security, compliance, payment information, electronic payments, ecommerce, security
     Globalscape
By: SAS     Published Date: Sep 30, 2014
When Information Revolution1 was published in 2006, no Chinese based companies were among the top 10 largest companies by market capitalization. Apple didn’t sell phones. Facebook was something college kids used to connect with their friends. Back then, we talked a lot about the amount of data coming in and faster processing speed. What we believed then remains true today: Data, and the decision-making process, can be moved throughout the organization to equip every decision maker (automated, line worker, analyst, executive) to make the best choices. By operationalizing analytics, organizations can identify and quantify both opportunity and risk. Information Revolution highlighted SAS’ Information Evolution Model, which helps organizations understand how they interact with their information and how to extract more value from it through analytics.
Tags : sas, organizational insights, operationalizing analytics, sas’ information evolution model
     SAS
By: SAS     Published Date: Feb 09, 2016
In this ebook, we provide some suggestions as to how firms might approach model risk measurement under the assumption that the firm has control over its broader information infrastructure, or at least is on a committed path toward that goal.
Tags : sas, white paper, information processing, best practices, model risk measurement
     SAS
By: iMarkup Solutions     Published Date: Aug 21, 2009
To optimize the processing of information in an enterprise, organizations need the tools to efficiently automate their existing processes and react quickly to changes in the environment. This is a primary objective of an electronic forms (eForm) processing solution.
Tags : project management, e-form, eform, eforms, e-forms, business process, bpm, business process management
     iMarkup Solutions
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