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Enterprise Ready Intelligent Capture (ERIC) — a coordinated approach to document input and processing that combines distributed and centralized scanning with fax and electronic conversion across numerous departments. Read on to learn more.

With key productivity applications becoming more bandwidth, processing and storage-intensive, dwp turns to Silver Peak Virtual Acceleration Open Architecture software to accelerate its file transfers and optimize WAN performance.

2014 sales success will be dictated by increasing efficiency and effectiveness of our sales teams. And important to note is how reps are currently spending time. We see that closing, processing and fulfilling orders takes about 50% of the time to get to yes in the first place. Read this whitepaper and explore advances in CRM 2.0 technology to optimize this aspect of selling.

In the age of Edward Snowden and the NSA, there are increasing concerns about data privacy and especially where best to keep data secure. The prevalence of cloud computing and cloud-based storage and collaboration services is only exacerbating these concerns. Many organizations are confused about regulations that protect data in different countries and jurisdictions, and don’t know what steps to take to ensure their cloud collaboration vendor can provide adequate safeguards. While pushback and reform efforts are evolving, the reality is that companies must operate within the law. Deciding where to house your data and how to move it is an exercise in understanding the relevant legal regimes and the application of risk analysis in the decision making process. This white paper will examine those elements with regard to cloud-based storage and processing.

For banks, mining data from social media can be a significant way to gain insights into customer mindsets and behavior, but effectively and accurately capturing and processing this unstructured data to gain useful customer insight requires sophisticated tools and advanced analytics.

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.

Read about what makes data warehousing as a service different from traditional data warehousing–it’s more than just a data warehouse in the cloud.

Six things that are critical to evaluate for data warehousing in the cloud.

Download this whitepaper to learn why many small and mid-sized firms are choosing a more robust outsourced solution that combines HR tasks, like time and attendance management and workforce administration, with traditional payroll processing to improve data accuracy, ensure regulatory compliance, and deliver greater economies of scale.

Today’s data, and how that data is used, have changed dramatically in the past few years. Data now comes from everywhere—not just enterprise applications, but also websites, log files, social media, sensors, web services, and more. Organizations want to make that data available to all of their analysts as quickly as possible, not limit access to only a few highly-skilled data scientists. However, these efforts are quickly frustrated by the limitations of current data warehouse technologies. These systems simply were not built to handle the diversity of today’s data and analytics. They are based on decades-old architectures designed for a different world, a world where data was limited, users of data were few, and all processing was done in on-premises data centers.

In today’s world of being “on” 24/7, data centers are at the core of business and viewed as the way to create competitive differentiation. Speed, efficiency, flexibility, and scale are now critical for winning the race to meet new connectivity and processing demands caused by the Internet of Things (IoT) and Big Data.

Find out how to meet the challenges facing your midsize company and benefit from the road map that takes you through the process of deploying a BI solution, enabling you to start small and then build incrementally on your initial success to make fact-based and BI-driven decision making pervasive in your company.

Examine how forward-looking firms are revamping their lead-to-cash process to impact what matters in the emerging economic environment: strong customer relationships and profitable growth. These firms are achieving a new level of process innovation and integration with powerful new software tools.

Discover how publishers, newspapers, studios, and broadcasting companies are using SAP solutions to automate the processes involved in acquisition and exploitation of content assets. They can accurately capture rights and effectively manage royalty processing for higher profits and better relationships.

Globalization has afforded great opportunities for companies who take advantage of them. Outsourcing is one of these, and payroll outsourcing is gaining popularity throughout the business world. Processing payroll in a timely and accurate manner is critical for business success. Maintaining salary, benefit, and tax information can be complex, which is why increasing numbers of small to medium businesses are choosing to outsource their payroll.

Most business owners realize the obvious benefits of outsourcing payroll, such as saving money: outsourcing payroll can save your company up to 30% over the cost of in-house processing. The first important step, of course, is finding the right payroll provider to meet your needs. This guide is designed to help you through that process with questions you should ask and criteria to consider when comparing payroll vendors

Optimize your business processes in the cloud with a next generation BPM strategy — an intelligent Business Platform (iBP) that implements an on demand, “service as you need it” model. Take advantage of Infrastructure as a Service (IaaS) for pure technology - processing, storage, networks with payment based on usage. Develop and manage business processes using the BPM Platform as a Service (BPMaaS), providing the BPMS tools supported by cloud services. Work with live business processes used by customers, suppliers, employees and trading partners, using Business Processes as a Service.

By using FTM, financial institutions can gain visibility into message processing, balance financial risk and facilitate effective performance management.

Consumers demand services according to their individual preferences whenever, wherever, and however they interact.

Learn about a solution for electronics manufacturers to promote greater efficiency and profitability, as well as consumer satisfaction. The full spectrum of IoT electronics consists of Medical Devices, Consumer electronics and appliances, network equipment providers and many more. “These “smart, connected products”—made possible by vast improvements in processing power and device miniaturization and by the network benefits of ubiquitous wireless connectivity—have unleashed a new era of competition.”

Read this Solution Guide to learn how to optimize monitoring & security for 40G & 100G networks While network owners are migrating to 40G & 100G infrastructures, most tools available today cannot ingest high-speed traffic. They lack both the physical interfaces and processing power to do so.

Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated drive as you read the morning news. We are getting very close to that kind of scenario, and companies like Ford expect to have production vehicles in the latter part of 2020. Driverless cars are just one popular example of machine learning. It’s also used in countless applications such as predicting fraud, identifying terrorists, recommending the right products to customers at the right time, and correctly identifying medical symptoms to prescribe appropriate treatments. The concept of machine learning has been around for decades. What’s new is that it can now be applied to huge quantities of data. Cheaper data storage, distributed processing, more powerful computers and new analytical opportunities have dramatically increased interest in machine learning systems. Other reasons for the increased momentum include: maturing capabilities with methods and algorithms refactored to run in memory; the

There is a lot of excitement in the market about artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). Although many of these technologies have been available for decades, new advancements in compute power along with new algorithmic developments are making these technologies more attractive to early adopter companies. These organizations are embracing advanced analytics technologies for a number of reasons including improving operational efficiencies, better understanding behaviors, and gaining competitive advantage.

When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics, and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. With the right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da

The 2016 ACFE Report to the Nations on Occupational Fraud and Abuse analyzed 2,410 occupational fraud cases that caused a total loss of more than $6.3 billion.8 Victim organizations that lacked anti-fraud controls suffered double the amount of median losses. SAS’ unique, hybrid approach to insider threat deterrence – which combines traditional detection methods and investigative methodologies with behavioral analysis – enables complete, continuous monitoring. As a result, government agencies and companies can take pre-emptive action before damaging incidents occur. Equally important, SAS solutions are powerful yet simple to use, reducing the need to hire a cadre of high-end data modelers and analytics specialists. Automation of data integration and analytics processing makes it easy to deploy into daily operations.