...Coffing Data Warehousing Education Outline 02/17/05 TERADATA EDUCATION OUTLINE Coffing Data Warehousing has provided quality Teradata education, products and services for over a decade. We offer customized solutions to maximize your warehouse. Toll Free: 1-877-TERADAT Business Phone: 1-937-855-4838 Email: mailto:CDWSales@CoffingDW.com Website: http://www.CoffingDW.com In addition to the course material listed in this outline, we also offer Teradata classes in Teradata Basics, Implementation, SQL, Database Administration, Design and Utilities. Please contact us so we can customize a course to fit your specific needs. © 2006 Coffing Data Warehousing – All rights reserved. Confidential. 1 Coffing Data Warehousing Education Outline 02/17/05 PURPOSE Coffing Data Warehousing has been providing quality Teradata education for over a decade. We offer customized courses to maximize the effectiveness of each class. The purpose of this proposal is to build a lasting relationship with your company. To this end, we have combined our comprehensive Teradata education services in a unique package that we feel best suits the diverse needs of your company while offering our high quality product at competitive pricing. Coffing Data Warehousing is excited to offer you, our preferred partner, an innovative new way to look at training at the CoffingDW Teradata University (CDW-TU). This approach provides the ability to maximize learning potential. Our goal is to make your employees...
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...Teradata Database Release Summary Release 12.0 B035-1098-067A March 2008 The product or products described in this book are licensed products of Teradata Corporation or its affiliates. Teradata, BYNET, DBC/1012, DecisionCast, DecisionFlow, DecisionPoint, Eye logo design, InfoWise, Meta Warehouse, MyCommerce, SeeChain, SeeCommerce, SeeRisk, Teradata Decision Experts, Teradata Source Experts, WebAnalyst, and You’ve Never Seen Your Business Like This Before are trademarks or registered trademarks of Teradata Corporation or its affiliates. Adaptec and SCSISelect are trademarks or registered trademarks of Adaptec, Inc. AMD Opteron and Opteron are trademarks of Advanced Micro Devices, Inc. BakBone and NetVault are trademarks or registered trademarks of BakBone Software, Inc. EMC, PowerPath, SRDF, and Symmetrix are registered trademarks of EMC Corporation. GoldenGate is a trademark of GoldenGate Software, Inc. Hewlett-Packard and HP are registered trademarks of Hewlett-Packard Company. Intel, Pentium, and XEON are registered trademarks of Intel Corporation. IBM, CICS, RACF, Tivoli, z/OS, and z/VM are registered trademarks of International Business Machines Corporation. Linux is a registered trademark of Linus Torvalds. LSI and Engenio are registered trademarks of LSI Corporation. Microsoft, Active Directory, Windows, Windows NT, and Windows Server are registered trademarks of Microsoft Corporation in the United States and other countries. Novell and SUSE are registered trademarks...
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...Testing, Implementation, Administration and Support using Data Warehouse/Data Mart Design, ETL, BI and Client/Server applications. * Certified in ICS PowerCenter Data Integration Developer Specialist 9.0 and Teradata 12 TE0-121 Certified Professional Program. * Extensively worked on Data Extraction, Transformation and Loading of data from various sources like Oracle, SQL Server, Flat files and COBOL Sources. * Worked extensively with Slowly Changing Dimensions. * Working knowledge of Teradata as a Developer with proficiencies in Teradata SQL Assistant utilities like Fastload, Multiload, BTEQ, FastExport, and Tpump. * Experience in Teradata Data Warehouse architecture. * Proficient in application development and support, for batch processes hosted on an IBM mainframe, with a core focus in COBOL, DB2, JCL and VSAM. * Hands on experience in performance tuning, resolving on-going maintenance issues and monitoring of production runs. * Data modeling using Erwin, Star Schema, Snowflake, FACT and dimension tables. * Hands on experience in UNIX shell scripting. * Excellent communication and interpersonal skills. TECHNICAL SKILLS Frameworks | Informatica Data Director (IDD), Informatica System Integration Framework (SIF), Teradata version 12, Mainframe z/OS | Application Modules | UNIX, Informatica Application Designer, Workflow Manager, Workflow Monitor, Repository Manager, Informatica B2B...
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...Refer your friends to the following positions. Division: AIM Requirement : Ab Initio Lead/ Architect Experience 5-10 years Qualification B.E/B. Tech/MCA/ME/M. Tech Candidate Requirement Primary : Ab Initio Secondary : Oracle 8i/9i RDBMS, PLSQL, Database Stored Procedures, Scripting skills with Unix Korn shell, Perl Candidates should have experience in following vicinity • System Analysis & Design • Strong Ab Initio ETL design skills • Involved in Ab Initio Design, Configuration experience in Ab Initio ETL, • Data Mapping, Transformation and Loading in complex and high-volume Environment and data processing at Terabytes level. • Capacity of designing solutions around Ab Initio, with advanced skills in high performance and parallelism in Ab Initio • Data warehousing implementation experience • Knowledge of Oracle 8i/9i • Strong analytical & problem solving skills • Strong UNIX, korn shell scripting experience. • Experience in leading a team of ETL developers • Experience in co-coordinating with offshore on development/ maintenance projects Work Location Bangalore, Chennai, Pune Requirement Cognos Lead/ Architect Experience 5-10years Qualification B.E/B. Tech/MCA/ME/M. Tech Candidate Requirement • Extensive Experience & Expertise on Business Intelligence, DW • Min. 3 years of hands on experience with Cognos toolsets, Cognos architecture. • Must have hands on experience on Cognos Report Studio , Cognos Analysis Studio , Metrics Studio , and Cognos...
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...THE DIGITAL SUPPLY CHAIN AND BUSINESS ANALYTICS by FRANCES STACKS Business analytics, data based decision making, data solutions – it goes by many names but is the lifeblood of many businesses. It is nothing new and certainly not a new concept that more effectively running a business makes a more successful and profitable business. Since the very first company came about, utilizing the information at hand to provide inventory, knowledge of customer needs, wants, and desires; it has been integral in sustaining a business and making it grow. As stated by Robert Jacobs and Richard Chase what we must recognize now is, “…so much more data is now captured and available for decision-making analysis than was available in the past.” To be sure, the sheer volume of data that is now available to companies is astronomical due to ever-expanding technology, application of complex mathematical models, and ever advancing ability to extrapolate mountains of data and whittle it down to useful knowledge for businesses. Where data was once available after the fact, a “post-mortem” approach, if you will, companies can now utilize data for analysis, forecasting, optimization, revising of business processes, more efficient decision-making, and ultimately (and conversely most important) greater customer satisfaction. Business analytics has moved from being a process of analyzing customer behavior after the fact to being a tool that can help predict customer behavior in the future. This is an invaluable...
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...DATA WAREHOUSE A data warehouse is a logical collection of information gathered from different operational databases and used to create business intelligence that supports decision making tasks and business analysis activities. Walmart is known for having the biggest data warehouse used, which is larger then 4 Petabytes. Wal-Mart is very secretive about their data warehouse. After achieving a major milestone Teradata, Wal-Mart’s data warehouse supplier, was given permission to announce a few shallow facts about Wal-Mart’s data warehouse. • Wal-Mart has indeed the world’s largest, non military, database with a size of one-half a petabyte. • It is the world’s largest data warehouse Wal-Mart keeps track of 100 million customers buying billions of products every week. Using this data allows Wal-Mart to achieve Always Low Prices. It is the data warehouse that enabled Wal-Mart to become one of the 15 most profitable companies in the world. Let’s look at some sales questions Wal-Mart’s data warehouse has to answer: • How much orange juice did we sell last year, last month, last week in store X? • Comparing sales data of orange juice in various stores? • What internal factors (position in store, advertising campaigns...) in- fluence orange juice sales? • What external factors (weather...) influence orange juice sales? • Who bought orange juice last year, last month, last week? A data warehouse really is a Decision Support System (DSS). Providing the data to support business decisions...
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...BUS211f(2) ANALYZING BIG DATA I1 Spring 2014—MW 8:00–9:20 am Location: Sachar 116 (International Hall) Prof. Bharatendra Rai 313-282-8309 (mobile) brai@brandeis.edu Office: Sachar 1C Hours: MW, 9:30 – 10:15 and by appointment TA: TBD This is a two credit module that examines the opportunities and industry disruption in an era of massive, high velocity, unstructured data and new developments in data analytic. We treat some strategic, ethical, and technical dimensions of big data. The technical foci of the course include data structures, data warehousing, Structured Query Language (SQL), and high-impact visual displays. The principal objective of the course is to help students build understanding of data as an essential competitive resource, and acquire advanced computer skills through cases and hands-on applications. Assignments and classroom time will be devoted to both to analysis of current developments in analytics and to gaining experience with current tools. Davenport , Thomas H. and Harris, Jeanne G. Competing on Analytics: The New Science of Winning. Cambridge: Harvard Business School Press, 2007. ISBN 978-1422103326. Available for purchase at the bookstore. There is a required on-line course pack available for purchase at the Harvard Business Publishing website at this URL: https://cb.hbsp.harvard.edu/cbmp/access/23455671 This link is also available on LATTE . See last page of Syllabus for course pack contents. Other readings as posted on LATTE site. Learning Goals...
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...Case Study: #1 - The Big Data Challenges Arnechia Washington Professor Durgin CIS500 Info Syst Decision-Making January 26, 2014 Volvo Car Corporation has incorporated the cloud infrastructure into its networks to globalize the company. “With hundreds of sensors and CPUs embedded throughout the car — from the brakes to the central locking system — data is now being captured for use within the vehicle itself, and also, increasingly, for transmission via the cloud back to the manufacturer” (Strader, 2011). Volvo’s data Warehouse has multi-terabytes of data from the hundreds of sensors and CPU’s that are embedded throughout the car as well as data from customer relationship systems. The Cloud platform allows implementing and evaluating real-time information systems to transform data into knowledge. This will give Volvo a competitive advantage over other car companies and allow their offices no matter the location to immediately take advantage of the data that is stored. There are two different cloud infrastructures within their infrastructure: service cloud and vendor hosting. Service cloud is used to support the customers and while their customers are operating the vehicles. This will enhance the car from the information that is gained based on the design and performance level of the car. Vendor hosting is used for the data that is located in separate warehouses. This platform allows the data to be consolidated into one place and reduces the cost to maintain, operate...
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...combined the use of different information systems into their business process, like most businesses today, but I will focus on their Decision Support System. I will explain how this Decision Support System is used in Wal-Mart and how this system has transformed how this organization operates. Then I will discuss some of the requirements that drove this system’s initial development. Next I will explain some of the basic uses of this system and how the system has help out Wal-Mart. I will also go over some of their future plans. Lastly I will conclude my paper and summarize some of my key points. System Use Marchela (2004), " Teradata, a division of NCR Corporation (NYSE: NCR), today announced that Wal-Mart has expanded its Teradata® data warehouse, increasing its lead as the largest retail data warehouse in the world” (para. 1). This Teradata warehouse was the basing for the company’s Retail Link decision support system between vendors and Wal-Mart. This grants suppliers to access large amounts of online, real-time data. This data helps those companies improve their operations. Jakovljevic (2005), " While Wal-Mart can match the growth of these retailers in absolute numbers just by opening new stores, it will hardly take more business in the competitive multichannel market serving customers with individual, personalized shopping experiences and by delivering on their complex requirements.” (para. 6). This type of thinking helped bring about more changes in the decision...
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...Week 3 - The Big Data Challenges May 2014 Case Study: The Big Data Challenges Glendoria Early Strayer University CIS 500 – Information Systems for Decision Making Dr. Vince Osisek May 12, 2014 Case Study: The Big Data Challenges Week 3 - The Big Data Challenges Page 2 What if your car could talk? Well Volvo CIO's had to wonder the same thing as well. Volvo, a Swedish multinational manufacturing company, that not only produce cars, but light and heavy weight trucks as well as buses. Volvo Car Corporation has a history of using innovation to produce premium automobiles. The manufacture chose to rely on information technology to gain the innovative edge to help the company grow by integrating the cloud infrastructure into their networks. The Volvo Data Warehousing Program, started in 2006 (Data in the Driver's Seat), it draws insight from this multi-terabyte resource to create clear business advantage by integrating information from four primary sources: a system for managing vehicle and hardware specifications, one for managing on-board software specifications, the system that collects vehicle diagnostic data from service centers worldwide, and the warranty administration system. (Tobey, 2010) Joining all the various pieces of data together, Volvo can be warned about potential mechanical issues that may show up in the early part of a car's lifecycle. Volvo can spot patterns from the data that may indicate a potential flaw in a particular part well before a...
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...Oracle 10g OCM Oracle 10g RAC Teradata Certified Certified Expert Masters (V2R5) Oracle 10g OCP Oracle 9i OCP ITIL V3 Certified Jagatsing Sursing Patil Email:- jagat_patil@yahoo.co.in Mobile+91-9320340010 Professional Summary Over all 16+ years experience in IT industries. 14+ years experience in Oracle 7,8i,9i,10g ,11g and Exadata engineering system. 2+ years experience in Teradata Database Administrator. Initial Level of experience in BIG Data Hadoop. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Expertise in proactively handling Oracle database issues to avoid major incident. Expertise in Root Cause Analysis and trouble shooting skills Expertise in mentoring database specialists and Handling Escalated calls. Expertise in providing solution within given SLA to avoid SLA bridge. Expertise in reviewing plan, risk and impact analysis before change. Expertise in implementing exact solution within given SLA. Expertise in providing exact solution during incident to avoid / reduce problem. Expertise in applying permanent fix to avoid problem. Expertise in providing different types of solution to migrate Non-Exadata into Exadata. Expertise in capacity management of databases according to their growth. More than 10 end to end RAC setup implemented in Oracle 10G and 11G on various platforms like RHEL ,SUN Solaris and AIX. More than 20 Dataguard setup implemented in Oracle 9i,10g and...
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...using the Internet. They want to use just-in-time supply chain methodologies. Companies want to use customer relationship marketing systems and have wireless access to corporate data. Instead of updates once a day, they want to be able to take a snapshot of their business more frequently.” The Internet has also added another dimension to database management, because knowledge management becomes more crucial as online customers require accurate, real-time information. "One of the problems with business-to-consumer e-commerce has been accuracy of data," Hammer says. "Some consumers were finding that they could not reliably order from online retailers, and that really hurt the business.” ETI recently introduced Accelerator for SQL/Teradata, which speeds the transformation and exchange...
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...THE BIG DATA CHALLENGES by William Thomas Info System Decision-Making Professor Raied Salman July 21, 2014 Volvo was founded in 1927 and, is one of the more popular brands of vehicles with over 400,000 cars sold in 2013. Their largest markets are the United States, Sweden, China, Germany and the UK. Volvo has taken vehicle diagnostics to another level by using the data transferred from their vehicles to improve the quality and performance of their overall fleet on the street and on the assembly line. In 1999 Volvo began collecting diagnostic read-out (DRO) data as a tool to help them get a better view into the performance and mechanical failure under actual field conditions. There are several factors to the diagnostic read- out that Volvo has to use in order for this information to be considered “useable data.” Diagnostic trouble codes (DTC) are generated when the vehicle presents some sort of fault, it is then stored in the engine control unit (ECU). The next step is where Volvo took the next in order to transfer data in knowledge. At a typical dealership the service technician would connect his code analyzer to the vehicle’s code output connection. He would then use this information in order to provide or suggest what type if any maintenance or repairs are needed. However; at a Volvo dealership, the data is transferred to a centralized database at the Volvo Headquarters commonly referred to as the “Data Warehouse.” This data is accessible to all Volvo dealerships...
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...BUS211f(2) ANALYZING BIG DATA I1 Spring 2014—MW 8:00–9:20 am Location: Sachar 116 (International Hall) Prof. Bharatendra Rai 313-282-8309 (mobile) brai@brandeis.edu Office: Sachar 1C Hours: MW, 9:30 – 10:15 and by appointment TA: TBD This is a two credit module that examines the opportunities and industry disruption in an era of massive, high velocity, unstructured data and new developments in data analytic. We treat some strategic, ethical, and technical dimensions of big data. The technical foci of the course include data structures, data warehousing, Structured Query Language (SQL), and high-impact visual displays. The principal objective of the course is to help students build understanding of data as an essential competitive resource, and acquire advanced computer skills through cases and hands-on applications. Assignments and classroom time will be devoted to both to analysis of current developments in analytics and to gaining experience with current tools. Davenport , Thomas H. and Harris, Jeanne G. Competing on Analytics: The New Science of Winning. Cambridge: Harvard Business School Press, 2007. ISBN 978-1422103326. Available for purchase at the bookstore. There is a required on-line course pack available for purchase at the Harvard Business Publishing website at this URL: https://cb.hbsp.harvard.edu/cbmp/access/23455671 This link is also available on LATTE . See last page of Syllabus for course pack contents. Other readings as posted on LATTE site. Learning Goals...
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...Data Warehousing Methodologies Using a common set of attributes to determine which methodology to use in a particular data warehousing project. DATA INTEGRATION TECHNOLOGIES have experienced explosive growth in the last few years, and data warehousing has played a major role in the integration process. A data warehouse is a subjectoriented, integrated, time-variant, and nonvolatile collection of data that supports managerial decision making [4]. Data warehousing has been cited as the highest-priority post-millennium project of more than half of IT executives. A large number of data warehousing methodologies and tools are available to support the growing market. However, with so many methodologies to choose from, a major concern for many firms is which one to employ in a given data warehousing project. In this article, we review and compare several prominent data warehousing methodologies based on a common set of attributes. Online transaction processing (OLTP) systems are useful for addressing the operational data needs of a firm. However, they are not well suited for supporting decision-support queries or business questions that managers typically need to address. Such questions involve analytics including aggregation, drilldown, and slicing/dicing of data, which are best supported by online analytical processing (OLAP) systems. Data warehouses support OLAP applications by storing and maintaining data in multidimensional format. Data in an OLAP warehouse is extracted and loaded...
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