The document discusses various types of computer systems and their uses. Microcomputer systems include personal computers and workstations used for tasks like CAD. Midrange systems are high-end servers that handle large-scale business applications. Mainframe computer systems are large, powerful systems used for tasks like large databases and e-commerce applications. The document also covers computer system concepts, processing speeds, peripherals, input technologies, output technologies, storage technologies, and optical disks.
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...Mihai Criveti
Automate your Data Science pipeline with Ansible, Python and Kubernetes - ODSC Talk
What is Data Science and the Data Science Landscape
Process and Flow
Understanding Data
The Data Science Toolkit
The Big Data Challenge
Cloud Computing Solutions
The rise of DevOps in Data Science
Automate your data pipeline with Ansible
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014MapR Technologies
View this webinar presentation as CenturyLink Technology Solutions (Formerly Savvis) and MapR as we deconstruct and demystify “the enterprise big data stack.” We provide you with a more holistic view of the landscape, explore use cases to show how you can derive business value from it, and share best practices for navigating through the fragmented big data environment.
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr...Dataconomy Media
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr. Abdourahmane Faye, Big Data SME Lead DACH at HPE
Watch more from Data Natives Berlin 2016 here: http://bit.ly/2fE1sEo
Visit the conference website to learn more: www.datanatives.io
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About the Author:
Abdou Faye is Subject Matter Expert in Big Data, Predictive Analytics / Machine Learning and Business Intelligence, with more than 19 years of experience in that area in various leading and executive roles, both from a Technical, Architecture and Sales perspectives. He recently joins HPE coming from SAP, where he was leading the Predictive Analysis & Big Data CoE (Center Of Excellence) business since 2010 for DACH, CEE and CIS region, in charge of Business Development and Sales Support. Prior to SAP, he worked 4 Years at Microsoft as Senior BI & SQL-Server Consultant in Switzerland, after 10 years spent at Philip Morris (CH), Orange Telco (CH) and SEMA Group (FR). Abdou graduated from Paris 11 University in 2000, where he completed a PhD on Data Mining/Predictive Analytics, after completing a Master in Computer Science.
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...Mihai Criveti
Automate your Data Science pipeline with Ansible, Python and Kubernetes - ODSC Talk
What is Data Science and the Data Science Landscape
Process and Flow
Understanding Data
The Data Science Toolkit
The Big Data Challenge
Cloud Computing Solutions
The rise of DevOps in Data Science
Automate your data pipeline with Ansible
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014MapR Technologies
View this webinar presentation as CenturyLink Technology Solutions (Formerly Savvis) and MapR as we deconstruct and demystify “the enterprise big data stack.” We provide you with a more holistic view of the landscape, explore use cases to show how you can derive business value from it, and share best practices for navigating through the fragmented big data environment.
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr...Dataconomy Media
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr. Abdourahmane Faye, Big Data SME Lead DACH at HPE
Watch more from Data Natives Berlin 2016 here: http://bit.ly/2fE1sEo
Visit the conference website to learn more: www.datanatives.io
Follow Data Natives:
https://www.facebook.com/DataNatives
https://twitter.com/DataNativesConf
Stay Connected to Data Natives by Email: Subscribe to our newsletter to get the news first about Data Natives 2017: http://bit.ly/1WMJAqS
About the Author:
Abdou Faye is Subject Matter Expert in Big Data, Predictive Analytics / Machine Learning and Business Intelligence, with more than 19 years of experience in that area in various leading and executive roles, both from a Technical, Architecture and Sales perspectives. He recently joins HPE coming from SAP, where he was leading the Predictive Analysis & Big Data CoE (Center Of Excellence) business since 2010 for DACH, CEE and CIS region, in charge of Business Development and Sales Support. Prior to SAP, he worked 4 Years at Microsoft as Senior BI & SQL-Server Consultant in Switzerland, after 10 years spent at Philip Morris (CH), Orange Telco (CH) and SEMA Group (FR). Abdou graduated from Paris 11 University in 2000, where he completed a PhD on Data Mining/Predictive Analytics, after completing a Master in Computer Science.
Watch full webinar here: https://bit.ly/3dhbZTK
What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Watch this session to learn:
- What data virtualization really is.
- How it differs from other enterprise data integration technologies.
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations.
Organizations have been collecting, storing, and accessing data from the beginning of computerization. Insights gained from analyzing the data enable them to identify new opportunities, improve core processes, enable continuous learning and differentiation, remain competitive, and thrive in an increasingly challenging business environment.
The well-established data architecture, consisting of a data warehouse, fed from multiple operational data stores, and fronted by BI tools, has served most organizations well. However, over the last two decades, with the explosion of internet-scale data, and the advent of new approaches to data and computational processing, this tried-and-true data architecture has come under strain, and has created both challenges and opportunities for organizations.
In this green paper, we will discuss modern approaches to data architecture that have evolved to address these challenges and provide a framework for companies to build a data architecture and better adapt to increasing demands of the modern business environment. This discussion of data architecture will be tied to the Data Maturity Journey introduced in EQengineered’s June 2021 green paper on Data Modernization.
Watch full webinar here: https://bit.ly/2xc6IO0
To solve these challenges, according to Gartner "through 2022, 60% of all organizations will implement data virtualization as one key delivery style in their data integration architecture". It is clear that data virtualization has become a driving force for companies to implement agile, real-time and flexible enterprise data architecture.
In this session we will look at the data integration challenges solved by data virtualization, the main use cases and examine why this technology is growing so fastly. You will learn:
- What data virtualization really is
- How it differs from other enterprise data integration technologies
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations
Are you having doubts and questions about how to use Big Data in your organizations? The presentation here would clear some of your doubts.
Feel free to comment if you have more queries or write to us at: bigdata@xoriant.com
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Do you have a true Big Data Analytics platform? What's a true Big Data Analytics platform? How can it help capitalize big data? What's needed to build one? This short introductory presentation can help understand what's a true Big Data Analytics platform and how it really helps building Big Data Analytics applications.
Watch full webinar here: https://bit.ly/3dhbZTK
What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Watch this session to learn:
- What data virtualization really is.
- How it differs from other enterprise data integration technologies.
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations.
Organizations have been collecting, storing, and accessing data from the beginning of computerization. Insights gained from analyzing the data enable them to identify new opportunities, improve core processes, enable continuous learning and differentiation, remain competitive, and thrive in an increasingly challenging business environment.
The well-established data architecture, consisting of a data warehouse, fed from multiple operational data stores, and fronted by BI tools, has served most organizations well. However, over the last two decades, with the explosion of internet-scale data, and the advent of new approaches to data and computational processing, this tried-and-true data architecture has come under strain, and has created both challenges and opportunities for organizations.
In this green paper, we will discuss modern approaches to data architecture that have evolved to address these challenges and provide a framework for companies to build a data architecture and better adapt to increasing demands of the modern business environment. This discussion of data architecture will be tied to the Data Maturity Journey introduced in EQengineered’s June 2021 green paper on Data Modernization.
Watch full webinar here: https://bit.ly/2xc6IO0
To solve these challenges, according to Gartner "through 2022, 60% of all organizations will implement data virtualization as one key delivery style in their data integration architecture". It is clear that data virtualization has become a driving force for companies to implement agile, real-time and flexible enterprise data architecture.
In this session we will look at the data integration challenges solved by data virtualization, the main use cases and examine why this technology is growing so fastly. You will learn:
- What data virtualization really is
- How it differs from other enterprise data integration technologies
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations
Are you having doubts and questions about how to use Big Data in your organizations? The presentation here would clear some of your doubts.
Feel free to comment if you have more queries or write to us at: bigdata@xoriant.com
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Do you have a true Big Data Analytics platform? What's a true Big Data Analytics platform? How can it help capitalize big data? What's needed to build one? This short introductory presentation can help understand what's a true Big Data Analytics platform and how it really helps building Big Data Analytics applications.
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Business Valuation Principles for EntrepreneursBen Wann
This insightful presentation is designed to equip entrepreneurs with the essential knowledge and tools needed to accurately value their businesses. Understanding business valuation is crucial for making informed decisions, whether you're seeking investment, planning to sell, or simply want to gauge your company's worth.
RMD24 | Debunking the non-endemic revenue myth Marvin Vacquier Droop | First ...BBPMedia1
Marvin neemt je in deze presentatie mee in de voordelen van non-endemic advertising op retail media netwerken. Hij brengt ook de uitdagingen in beeld die de markt op dit moment heeft op het gebied van retail media voor niet-leveranciers.
Retail media wordt gezien als het nieuwe advertising-medium en ook mediabureaus richten massaal retail media-afdelingen op. Merken die niet in de betreffende winkel liggen staan ook nog niet in de rij om op de retail media netwerken te adverteren. Marvin belicht de uitdagingen die er zijn om echt aansluiting te vinden op die markt van non-endemic advertising.
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
45. SOFTWARE HARDWARE SYSTEM SOFTWARE APPLICATION SOFTWARE OPERATING SYSTEM: LANGUAGE TRANSLATORS: UTILITY PROGRAMS: PROGRAMMING LANGUAGES:
46.
47.
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49. Multi - Tasking OPERATING SYSTEM UNUSED MEMORY PROGRAM 1 TRADITIONAL SINGLE-PROGRAM SYSTEM OPERATING SYSTEM UNUSED MEMORY PROGRAM 1 PROGRAM 2 PROGRAM 3 MULTIPROGRAMMING ENVIRONMENT
84. TYPES OF INFORMATION SYSTEMS DATA WORKERS KIND OF SYSTEM GROUPS SERVED STRATEGIC LEVEL SENIOR MANAGERS MANAGEMENT LEVEL MIDDLE MANAGERS OPERATIONAL OPERATIONAL LEVEL MANAGERS KNOWLEDGE LEVEL KNOWLEDGE & SALES & MANUFACTURING FINANCE ACCOUNTING HUMAN RESOURCES MARKETING
108. Data collection Data edit Data manipulation Data storage Document production Data correction Original data
109.
110. Point-of-Sale Transaction Processing System Customer’s receipt Inventory database Management information system Exception report Purchases database Scanner Point-of-sale transaction processing system Item database UPC and quantity Item, quantity, date, time, price UPC Price UPC Quantity, Date, time
111.
112.
113. Customer Order entry/ sales configuration Shipment planning Routing Scheduling Shipment execution Invoicing Finished product inventory Customer order in person or via mail, phone, EDI, internet Orders Planned shipments Planned shipments & routes Pick list Shipped orders Inventory status Products Invoice
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120. Request for proposal Sale Problem, idea, request for information Other contacts Market research Sales Marketing Quality control Product development Customer interaction system Customer
123. Raw materials Packing materials Spare parts Inventory control Purchase order processing Receiving Accounts payable Employees Supplier Inventory control status report Purchase order Material Cheque Invoice Receiving notice Purchase order Purchase order request
127. Customer Accounts receivable Asset management Accounts payable Payroll Budget Customer General ledger Time cards Paycheques Labour costs Expense transactions Asset depreciation Amounts owed by company Amounts paid by company Cost of assets Payments Amounts owed by customers Amounts paid by customers
135. ERP Examples Software Vendor Name of Product Avalon Software Avalon CIM qad.inc MRG/PRO Oracle Oracle Manufacturing SAP America SAP R/3 Baan Triton PeopleSoft PeopleSoft J.D. Edwards World
205. Introduction to E-Business The terms Internet, electronic commerce, electronic business, and cybertrade are used often. However, they are used interchangeably and with no common understanding of their scope or relationships.
241. Objects Objects can be described by their attributes and operations. Attributes are the changeable characteristics of an object. Cats have colou
Editor's Notes
These facts should be a wake-up call to web-enabled companies that there is a real service gap to address and that additional profits await those companies who quickly find a way to fill this gap. ECRM can help companies meet this challenge. The convenience of shopping on-line may bring customers in through the virtual door, but what keeps them coming back through that same door is the overall quality of the customer experience. Web-enabled organizations need to understand this, because the cost of marketing to an existing customer is $6.80 over the Internet versus $34.00 to attain a new web customer (Karpinski 2001). Investing in ECRM solutions will give companies the tools they need to create, maintain and extend competitive advantage in their market spaces. Having here established the ECRM imperative, this paper will detail the benefits of ECRM systems and discuss the five focal points to consider before implementing an ECRM solution.
A recent McKinsey & Co. study revealed that a 10% gain in repeat customers can add about 10% to the company’s profits. On the other hand, a 10% reduction in the total marketing expenditures needed to attract new visitors adds only .7% to the bottom line (Sims 2000). In essence, keeping existing customers happy is more profitable than going after greater numbers of new customers, even when a company is able to pare down the cost of attracting new customers. The best way to keep one’s existing customers happy is to deliver value to them on their own terms (Jutla et al. 2000). Anderson Consulting found that as much as 64% of the difference in return on sales between average and high performing companies is attributable to ECRM performance (Sims 2000). Improvements in the overall customer experience lead to greater customer satisfaction, which in turn has a positive effect on the company’s profitability. The following benefits can be realized with proper ECRM implementation:
Increased customer loyalty: An effective ECRM system lets a company communicate with its customers using a single and consistent voice, regardless of the communication channel. This is because, with ECRM software, everyone in an organization has access to the same transaction history and information about the customer. Information captured by an ECRM system helps a company to identify the actual costs of winning and retaining individual customers. Having this data allows the firm to focus its time and resources on its most profitable customers (epiphany.com). Classifying one’s “best” customers in this way allows an organization to manage them more efficiently as a premium group, with the understanding that it is neither necessary nor advisable to treat every customer in the exact same way. One tool that a company can implement in pursuit of customer loyalty is personalization (Waltner 2001). Personalization software tools generate real-time profiles for each customer using data from many sources including customer databases, clickstream data and transaction systems. The tool selects the best offer each time a particular customer shops the company’s web site based on what it “knows” about that customer. As an individual accepts or declines an offer, the personalization engine builds this knowledge of the customer into his/her profile, making it available for better-informed future offers (Greenberg 2001).
More effective marketing: Having detailed customer information from an ECRM system allows a company to predict the kind of products that a customer is likely to buy as well as the timing of purchases. In the short to medium term, this information helps an organization create more effective and focused marketing/sales campaigns designed to attract the desired customer audience (epiphany.com). ECRM allows for more targeted campaigns and tracking of campaign effectiveness. Customer data can be analyzed from multiple perspectives to discover which elements of a marketing campaign had the greatest impact on sales and profitability, for example (Greenberg 2001).
Improved customer service and support: An ECRM system provides a single repository of customer information. This enables a company to serve customer needs quickly and efficiently at all potential contact points, eliminating the customer’s frustrating and time-consuming “hunt” for help (epiphany.com). ECRM-enabling technologies include search engines, live help, e-mail management, news feeds/content management and multi-language support. With an ECRM system in place, a company can: more accurately receive, update and close orders remotely log materials, expenses and time associated with service orders view customer service agreements search for proven solutions and best practices subscribe to product-related information and software patches and access knowledge tools useful in completing service orders (peoplesoft.com). All of these expanded capabilities work together to keep the customer right where s/he belongs: at the center of the company’s attention.
Greater efficiency and Cost Reduction: Automating customer data mining saves valuable human resources. Integrating customer data into a single database allows marketing teams, sales forces, and other departments within a company to share information and work toward common corporate objectives using the same underlying statistics (epiphany.com). Examples of this are identifying unproductive/underutilized resources, closer tracking of costs, better forecasting for the pipeline and setting realistic project metrics and measurements to quantify return on investment.
. Developing customer focused business strategies: The objective of this step is not to try to mold the customer to the company’s goals but to listen to the customer and try to create opportunities beneficial to each. It is important to offer customers what they are currently demanding and anticipate what they are likely to demand in the future. This can be achieved by providing a variety of existing access channels for customers, such as e-mail, telephone and fax, and by preparing to provide for future access channels such as wireless communication.
Retooling business functions: Starting to do business via ECRM will require disruptive organizational change in order to determine which departments/functions are truly servicing the customer and which ones are only adding to overhead. After identifying and trimming redundant head-count, administrative time and cost should drop. A major factor here is that the changes required during an ECRM implementation will only be possible with buy-in from the top levels of management and with company-wide accountability of all stakeholders. It is the responsibility of senior management to ensure that all employees understand the necessity of the changes, how the new structure will benefit them, and how it will enhance their ability to serve their customers.
. Work process re-engineering: The departmental role and responsibility changes from retooling business functions will necessitate adopting new work processes. The choices here are to take the traditional step-wise approach or an integrated one toward improving work efficiency. Under the step-wise approach, departments are treated as separate efficiency entities. This rarely produces good results because the goals of each department can become too parochial, and departments tend to compete internally for their own benefit at the expense of what’s best for the company. We recommend the integrated approach. It tends to produce superior results because it recognizes the interdependencies among the company’s multiple functions/departments and how these create the larger perspective of the entire organization.
Technology choices: The focus here is to consider the company’s industry, the company’s position within its industry, and which ECRM configurations are good candidates for the company in particular. Criteria for technology selections include: scalability of software tool set flexibility for customization stability of the existing ECRM application code compatibility of ECRM application with legacy and internet systems level of technical support available during and after implementation
upgradable support the availability of additional modules (Sims 2001). We cannot stress enough that an in-depth study of the compatibility of the proposed ECRM system with a company’s existing ERP system is absolutely essential. Customer-facing applications must be coherently linked to the transactions that they generate behind the scenes. Without integration of ERP and ECRM systems, organizations risk redundancy of data, increased response times and loss of customers due to delays and botched transactions. With such integration, however, improved business intelligence is possible by capturing data at every point of customer contact, from order-entry to fulfillment, via multiple media channels (White 2000).
Training and Preparation: This focal point is arguably the most important one in ECRM implementation. Training of employees should occur before the new ECRM system has been implemented to ensure a seamless transition for customers. Anyone who requires access to the system should receive full, appropriate and timely training. Training should be an ongoing, managed activity as systems must continuously change and evolve. All training and tools used should be thoroughly documented for current, new and future employees. Without a documentation management scheme, the value of the ECRM system could degrade rapidly. A firm should plan to spend about 5% of its total ECRM implementation on training (computerworld.com).
Paul Horstmeier, newly appointed e-marketing manager of Hewlett-Packard, quickly discovered that the computer industry giant had made a muddle of its attempts at e-mail marketing (Patton, 2001a). The company’s typical customers include IT managers who have purchased servers, printers and services before. HP had been launching separate, uncoordinated e-mail campaigns from nine different marketing groups. Horstmeier saw that in order to provide useful benefits to HP, his group needed to take over management of the e-mail campaigns from the nine different marketing groups. It also had to promote the idea that marketing should be a long-term process that focuses on the life cycle of customers instead of looking at a sale as a one shot transaction. This demanded that Horstmeier’s group focus on the e-mail marketing operation while coordinating its efforts with the larger corporate structure that included other customer-facing groups like call centers and customer service teams. To meet these integration needs, the e-marketing group brought in e-mail analysis, segmentation and personalization tools from San Mateo, CA based Digital Impact. By analyzing its e-mail databases, HP found that its business customers fell into two groups; IT managers and end users. Rather than flooding the two segments with immediate additional e-mail campaigns, HP started to learn what these groups wanted through small pilot tests. The company found that IT managers were willing to tell HP exactly what kinds of general product support alerts and newsletters they’d like to get (such as laptop discussion forums, print driver updates, and new product introductions) whereas end users wanted more specific information about the exact product that they had bought (network server, PC or printer model number) and how to use it. H.P.’s results showed that more of their customers responded to the low-cost e-mail offer than to the direct mail offer, making the e-mail offer both more productive in terms of sales generated and more cost-effective in terms of expenses saved. Customers also said they liked getting the e-mail alerts and updates with more than 85% saying they were quite satisfied with the content that they received. The e-mail campaigns generate an estimated $15 million in new monthly sales revenues, as well as half a million dollars in monthly cost savings from the consolidated e-mail campaigns. By sending out product support alerts and e-mails, the resulting reduction in calls made to support lines saves nearly an additional $150,000 per month (Patton, 2001a).
ECRM has arrived and whether or not the name remains, the concept is here to stay. We have identified the five critical issues that companies must consider at the threshold of ECRM implementation. We have also explored the customer-centric and corporate benefits of implementing an ECRM solution, with the understanding that ECRM efforts will only succeed when organizations make their customers win. Increasingly, the information age has inspired a new breed of customer who is not willing to take “No” for an answer when the question is: “Will your company use its talent and resources to allow me to pull from it the products and services I need in order to be productive in my professional and private life?”. ECRM solutions give companies the power to say “YES!”. The very survival of these organizations depends on their commitment to this answer.
The preceding case studies show a direct relationship between political conflicts and increased cyber attack activity. Further, they highlight that this malicious cyber activity can have concrete political and economic consequences. In the Israel/Palestinian conflict, following events such as car bombings and mortar shellings, there were increases in the number of cyber attacks. Subsequent to the April 1, 2001 mid-air collision between an American surveillance plane and a Chinese fighter aircraft, Chinese hacker groups immediately organized a massive and sustained week-long campaign of cyber attacks against American targets.
The cyberwar strategy relies on hacking, virus writing, electronic snooping and plenty of good old-fashioned human spying. Much disruption can be unleashed over the Internet, but attackers first need to pry open electronic gates to private and secure networks with well-placed insiders, or at least inside knowledge, before they can be effective. Source: Far Eastern Economic Review , Copyright (c) 2001, Dow Jones & Company, Inc., Thursday, August 16, 2001, Innovation, Cyberwar, Combat on The Web; Charles Bickers in Tokyo
... a Hewlett Packard printer at the Navy's Space and Naval Warfare Systems Command Center (SPAWAR) in San Diego was reportedly reprogrammed to print out additional copies of all documents to a printer in Russia. Domain Name Service (DNS) attacks are ones we have not paid much attention to. The vulnerability at the local level is very high by a malicious insider. Lack of cyber diversity increases the chances of a simple but widely effective attack. Routing Vulnerabilities. Example - Possibly attacking the border gateway protocol (BGP) which routers use to made decisions about where to sent traffic on the Internet. This protocol is vulnerable to information poisoning that could corrupt routing tables. The result of this action would be a very effective Internet 'black hole' where large volumes of information header for destination all over the world would be lost.
California Independent System Operator Berkowitz source: http://www.nap.edu/issues/17.2/berkowitz.htm Information Warfare: Time to Prepare Cooperation between the government and industry is essential to protecting the nation's information infrastructure.