Enterprise Data Systems
UNC Greensboro ISM 611
November 8, 1999
NCR Corporation
Data Warehousing Solutions Provider
Presented by:
Dave Raspberry
Cheng Murray-Khoo
Eric Braun
NCR Corporation
Data Warehousing Solutions Provider
NCR Overview
John Patterson founded NCR in 1884. It is one of the oldest computing companies in the
world. NCR began as a cash register company, and this success led NCR to enter the
computer business in 1960. In 1990, AT&T bought NCR, while NCR was acquiring
Teradata Corporation.
The acquisition of Teradata was a very important step in the history of NCR. Teradata
provided NCR the first platform for what has come to be known as data warehousing. A
major reason for this development was the first commercially available massively parallel
processing hardware system (MPP), and it was called The Teradata Database Computer.
Purchasing Teradata strengthened NCR offerings in the high-end arena. In addition, NCR
began offering an entire group of products based on the Intel chip. This platform has
come to be known as the NCR Worldmark series, and it provides symmetrical processors
(SMP), clustered systems processors, and the scalable open systems (MPP) with Intel
technology.
Data Warehousing is fast becoming NCR’s primary business. They are positioning
themselves as a data warehousing/decision support solutions company. Software and
services are becoming a dominant part of the company. Until recently, NCR had most of
its success in major accounts requiring large databases. Now the company is going after
small and large companies using the approach Teradata can work for small companies
and large companies who want to start small.
NCR, Teradata , and Parallel Processing
What makes NCR different is its reliance on Parallel Processing, primarily on ER database
models. This is very different from their competitors, who use star schema designs.
Teradata spreads the database among the many processors. The optimizer is designed
to analyze a request and create a plan to service it. The other processors execute the
plan simultaneously on their part of the database. There could be 200 processors, each
working on a separate gigabyte from a table, instead on one processor working on 200
gigabytes.
NCR’s strategic approach to data warehousing is based on three factors: performance,
scalability, and ease of setup and support.

Performance: The parallel approach is the reason that NCR is able to handle the
world’s largest databases for decision support. Teradata is fully parallel during the
load, processing and back-up routines in the business. Also, Teradata’s optimizer
allows it to handle this environment without database or query tuning. Also, it allows a
variety of database models. Teradata can use 3rd normal form, star schemas,
denormalization, or a combination. Therefore, you are not constrained by technology
and are free to model to your business needs.

Scalability: If a data warehouse is implemented correctly, it will tend to grow because
of popularity in the user community. On the average, data warehouses double in size
each year. Teradata allows a company to start small and grow by easily adding
tables or servers. It is this scalability that allows companies to query large volumes of
detail data using Teradata. Most companies selling systems based on star schemas
do not advocate detail data because of the massive volume. However, Teradata was
designed for detail data.

Ease of Setup and Support: Teradata only requires two system administrators to
run it. Teradata does not require reorganizations, automatically places data evenly
across the nodes and processors, and utilizes parallel processing utilities to load and
archive data. As the volumes increase, the administrator’s workload does not. WalMart’s 24TB warehouse has over 6000 users, many of whom can request complex
queries, receives 3,500 source feeds daily while queries are running. They only have
two full-time DBA’s.
While detail data is very important for analysis, creating data marts for summarized data
requests can enhance performance of the warehouse. Teradata can provide both detailed
and summarized data, and accomplishes this by extracting data marts from the central
data warehouse detail data or from load utilities.
The NCR Teradata RDBMS is the only database on the market that processes data and
backs-up data in parallel. Teradata spreads the database evenly among hundreds of
processors, and each processor is responsible for processing a different portion of the
database. These processors work in unison when a request is made on their respective
portion of the database.
NCR’s Scalable Data Warehouse Framework
NCR has implemented over 800 data warehouses. NCR has developed a “Scalable Data
Warehouse (SDW) Framework” which is used to solve the business problems. This
approach involves IT resources, the technologies involved, the processes, and the
businesses involved.
The SDW framework can accommodate the implementation of either independent data
marts or directly building a scalable data warehouse with dependent data marts. These
data marts can be included in the Teradata enterprise warehouse, or configured across a
network. This approach gives the company the ability to expand the business model and
the data model, and to make management of the environment easier.
The goal of a data warehouse is to co-exist with the existing transaction based database,
while extracting key operational data from those systems for use in a centralized, relational
database. What data is considered critical depends on the particular business and is
defined in those terms. Usually, it is the data generated by the business about such
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operations as sales, shipping, orders, production, or customer information. To achieve
this informational data, it is necessary to perform transformation on raw operational data.
One of the greatest challenges to building a SDW framework is the process of
transforming operational data into informational data that is needed to add value to the
business. However, this process is critical for success. What makes this process so
difficult is the fact that operational data frequently has been customized and designed to
maintain only that particular business unit. Often, it has been organized without taking into
account how the other parts of the organization handle their data. In addition, the manner
of updating the data is usually different, and there may be some data that has been
accumulated through the years and has not been updated.
When building a scalable data warehouse, NCR recommends starting with a smaller,
more manageable enterprise data warehouse, which focuses on one or two areas. Also,
NCR recommends that dependent data marts be a part of the architecture of the
warehouse, and thus, a part of the enterprise strategy. As a smaller version of the data
warehouse, the dependent data mart provides the user with accessibility to the data,
where they can quickly get answers to their queries. These logical data marts seem to be
a special data warehouse to the user, but are actually a part of an integrated enterprise
environment.
The goal of a scalable system has four dimensions, which allow the maximum number of
users the ability to extract data while running complex queries against complex data
models with minimal support:

The ability to input and extract data with consistent response times

The number of users or queries that can be run simultaneously

The environmental complexity of the data model and the queries being run against the
model

The degree of support needed to maintain scalability.
These systems use industry standard rack mount architecture. They consist of individual
subsystem chassis that are housed in standard rack frames. Subsystems are selfcontained and their configurations are redundant.
Processing rack subsystem chassis include the following:

Symmetrical multi-processing (SMP) node

BYNET interconnect subsystem

Service subsystem

Uninterruptible power supply (UPS)
NCR’s Logical Data Model Philosophy
NCR’s approach to defining a logical data model is called Third Normal Form. During the
modeling process, one tries to resolve non-specific relationships between entities. This is
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called normalization. Normalization minimizes redundancy and structures the data in its
most basic form. As the model is refined, it passes through different states that are
referred to normal forms. At third normal form, all attributes in a table are dependent on
the key field of that table only. There is no redundancy, or repeating items, and there is no
derived data.
NCR believes that data models built on the star schema design limit business intelligence.
This is because of assumptions in the star schema design. The star schema approach
makes certain assumptions about data, presuming to know relationships among data in
advance. For example, if the company looks at sales data only by how sales have done
the past week, the assumption is that there is no variation in days or hours of the day.
Also, it is assumed that customer’s behavior is even and predictable throughout the week.
One of the ways assumptions are made is through denormalization, which reduces the
complexity of the information so that a DBMS can handle it better. Denormalizing helps
the DBMS, but it decreases the quality of the information.
Utilizing third normal form for both the logical and physical aspects of the computer models
minimizes the need to denormalize the data. It avoids the data integrity compromises that
can lead to business problems.
One disadvantage of a normalized model is the extreme number and complexity of the
tables. Since the model does not make any assumptions about how the users will use the
data, any relationship that is a business possibility is also possible in the model. However,
NCR believes that the many tools on the market available to end-users allow them to have
no knowledge of how the data is stored and, through the use of metadata and the tools,
be able to request answers to business questions that are changed into SQL queries by
the tools.
NCR’s philosophy is that denormalizing tables is detrimental to the process. It is their view
that it is done to gain performance to known requests. In order to denormalize, one must
know what the users are going to request, and the logical model is compromised for the
sake of performance, or the limitations of the front-end tools. To get performance from
third normal form, one needs a database that has the ability to handle the four hardest
things for a database:

Join tables

Aggregate data

Sort data

Scan large amounts of data
NCR’s databases handle these limitations by the use of total parallelism and the use of a
cost based optimizer. The optimizer is able to view all the options of the query and decide
the least costly. It is NCR’s viewpoint that if users want to ask any question of the data,
then star schema approaches are not going to provide the best performance. If you only
want answers to well-known queries, then the star schema approach should work fine.
But this is truly not practical for most companies, for the data warehouse was built to allow
users to perform ad hoc queries against any data for analysis to solve problems. These
queries may not be known at the design time of the database.
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WorldMark Servers
NCR Teradata uses massively parallel-processing technology to split the work among
hundreds or thousands Intel microprocessors, depending on the needs of the user. The
NCR Teradata RDBMS is available for UNIX or Windows NT. Teradata also supports the
current SQL standard and also, ODBC, and X/OPEN XA standards. Teradata works with
other UNIX systems, IBM mainframes, Macintosh, and Windows servers and clients.
NCR has designed four generations of large and medium scale servers for the data
warehousing enterprise. WorldMark servers are designed for optimal utilization of
Teradata architecture and NCR’s BYNET technology in a decision support environment.
The most recent servers are the 4800 and the 5200. They became available this year,
and operate with the latest Intel microprocessing technology.
WorldMark 4800 servers offer the ability to enter the data-warehousing arena for
applications ranging from 50 Gigabytes to 1 Terabyte. These massively parallel
processing servers are designed to run with the Teradata database, to give an integrated
data warehouse solution. This system is scalable and when maximum capacity is
reached, it can be upgraded to the WorldMark 5200. The system is expandable from 1 to
8 nodes. The 5200 is designed specifically for large-scale data warehousing, and is
capable of supporting applications from 400 Gigabytes to more than 100 Terabytes. This
system is scalable and will expand from 2 to 512 nodes.
Teradata Relational Database Management System (RDBMS)
The NCR Teradata RDBMS is the most powerful decision support, parallel, relational
database that is available in the market. It offers enterprise decision support scalability
from gigabytes to terabytes, to petabytes, and beyond. It is the only database product that
realistically supports data warehouses in excess of 500 gigabytes of user data.
NCR Teradata RDBMS runs on Intel-based UNIX and Windows NT platforms. In fact,
NCR just successfully ported its powerful Teradata database to Windows NT operating
system in October 1998. Both versions of Teradata run on different operating platforms
and have the same industrial-strength features, functions and capabilities.
The hardware that supports the Teradata software is based on off-the-shelf
microprocessor technology combined with a proprietary communications network,
BYNET, connecting the microprocessor elements.
Teradata software runs on both Symmetric Multiprocessing (SMP) and Massively Parallel
Processing (MPP) hardware platforms. The components of the machine include:

Processor node
It is the basic hardware-processing unit. For example, an SMP machine comprised of
a single processor node with the following:



Database software
Client interface software
Operating system
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


Multiprocessor shared-memory processors
RAID disk arrays
Failsafe power provisions
Whereas an MPP machine is a configuration of two or more loosely coupled SMP
nodes with shared SCSI access to multiple disk arrays.

BYNET
It is an inter-processor network to link nodes in MPP system (or VNET on single node
SMP system). It serves the function in connecting processors by broadcast, multicast,
or point-to-point communication, depending on the situation.
The Teradata software, as a complete relational database management system, attaches
directly to an I/O channel of a mainframe computer or intelligent workstations via a LAN.
Data stored can be accessed and operated using Teradata Structured Query Language
that broadly compatible with IBM and ANSI SQL.
The software architecture is best explained using diagramming approach as below.
Teradata RDBMS Architecture Overview
The process flow of an SQL statement through the Teradata RDBMS helps in
understanding the Teradata software architecture.
Assumptions made in simplifying the explanation:


The Teradata RDBMS runs on Windows NT platform in SMP (single node) system.
The network link is by means of LAN connection using either TCP/IP or ISO/OSI
protocols.
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Step 1
User generates an SQL query on the LAN-attached client system. The query can
originate from within an application program coded in a host language, or from a
compatible fourth generation language.
Step 2
The Call-Level Interface (CLI), the principal API for Teradata RDBMS, packages the SQL
request which routes to the server by Teradata Director Program (TDP).
Step 3
TDP, the data communication manager, establishes a session between the server and
client, then routes the request across the communications channel to the parsing engine
(PE).
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Step 4
The PE is a processor that communicates with the client system at one side and with the
Access Module Processes (AMPs) on the other.
There are three major components in PE:

PE performs session control. PE establishes a session only if it can validate the
username, password and user type from the client. User type refers to application
program or third party software products.

The SQL parser of PE opens the request package and parses the SQL codes for
processing. The parser interprets the codes, checks for syntax error, evaluates the
semantics, and converts database, table, view, and macro names to numeric
identifiers to produce lists of objects and access right. The built-in optimizer
determines the most effective way to access the data. The output at this stage is the
concrete steps. The steps are directives to the database management system that
contain user and session-specific information as well as data parcels.

The dispatcher of PE sequences the execution of the steps. It passes the steps on to
the BYNET (or VNET on single node system) with instructions about whether the
steps are for one AMP, an AMP group, or for all AMPs.
Step 5
BYNET, the inter-processor network, distributes the execution steps to the appropriate
AMP for processing.
Step 6
Access Module Process (AMP) is the heart of Teradata RDBMS. It is a virtual processor
(VPROC). Multiple VPROS can run on a SMP node.
The versatility of Teradata RDBMS is based on virtual processors (VPROCS). VPROCS,
NCR’s patented technology, is the software processes that emulate physical processors
and act as the basic “unit of parallelism” within the parallel database system.
Besides interfacing with BYNET, each AMP executes the database software to perform
relational functions and data management. It provides the following functions:





Data access
Concurrency control
Journaling
Cache management
Recovery management
Each AMP controls a portion of database. Each AMP maintains its own portion of
database tables stored on the disks. AMP then uses the file system software to control
the read and write of data on its disk.
After receiving the execution steps via BYNET interfacing, AMPs process the steps by
performing operations on the database by making calls to the file system.
Step 7
The file system performs primitive physical data block operations. It translates AMP
reads, and translate AMP row requests into physical data block requests and passed them
to disk subsystem.
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Step 8
The disk subsystem retrieves the requested blocks for the file system.
Step 9
The disk manager returns the requested blocks to the file system.
Step 10
The file system returns the requested data to the database manager.
Step 11
The database manager sends a message back to the dispatcher stating that data is ready
to be returned to the requesting user, then sorts and transmits the data to the interface
engine over the BYNET.
Step 12
The BYNET merges the sorted responses and returns it to the requesting interface engine
for packaging.
Step 13
The dispatcher builds the response message and routes it to the communications channel
driver for return to the requesting client system.
Step 14
The TDP receives and unpacks the response messages and makes them available to
CLI.
Step 15
CLI passes the received data back to the requesting application in blocks.
Step 16
The requesting application receives the response data in the form of a relational table.
Scalability – the Cornerstone of Teradata RDBMS
Six of the world’s 10 largest DSS databases use the NCR Teradata RDBMS. Teradata is
the proven industry leader for data warehousing with production sites ranging from 10GB
data marts to more than 24TB enterprise data warehouses.
What differentiates Teradata from other data warehousing solutions is the ability to scale
and support warehouses as small as four processors, up to some of the world’s largest,
with over a thousand processors.
Scalability is possible with Teradata’s “Shared Nothing” architecture coupled with Teradata
software and BYNET connection.
Teradata maximizes the processing of single node, whether it is on UNIX or Windows NT,
by its patented share-nothing technology known as Virtual Processors, VPROCS (Please
refer to step 6 of Teradata RDBMS Architecture Overview section for details).
In addition, Teradata provides linear scalability where customers can incrementally add
SMP nodes together using BYNET interconnection. BYNET is a redundant, fault tolerant,
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intelligent, high speed circuit switching interconnect. BYNET enables Teradata to
coordinate and synchronize the activities of a large number of SMP nodes. This can be
done without much increase in network traffic or degradation of the system’s performance.
BYNET can linearly scale to support up to 4096 nodes. Once connected, all nodes
become part of a large complex managed as a single system.
This further fulfilled the principal goal of the design of Teradata RDBMS, the principle of
Shared Information Architecture (SIA). SIA refers to a single data store for any number of
client architectures. There are no duplicate databases on multiple platforms. This greatly
reduces the maintenance cost of the data warehouse.
NCR’s Data Warehousing Alliance Partners
NCR recognizes that customers' needs, from a business and technology perspective, are
so diverse that no single company can meet them alone. So, they use strategic
partnerships to provide synergy for delivery of their offerings. The alliances between NCR
and their partners enable customers to choose from a full suite of data warehousing tools,
applications and software products. NCR groups their strategic partners into categories of
their application:
Customer Relationship Management (CRM) Applications
These providers integrate specialized business applications that leverage the power
Teradata provides in terms of detail customer data. These companies include Ceres Integrated Solutions
 Exchange Applications
 Prime Response
Data Transformation
Transformation activities may include accessing, reconciling, capturing, conditioning,
extracting, condensing, filtering, house holding, scrubbing and loading. NCR offers many
of these tools, but recognize that a successful transformation process still requires
experienced and knowledgeable consultants to ensure proper implementation. These are Carleton Corporation
 Evolutionary Technologies International
 Prism Solutions, Inc.
 SAS Institute, Inc.
 Trillium Software
Enterprise Warehouse Tools
The goal of the enterprise warehouse is to provide a single data store of clean, accurate
detail and summary data for the enterprise – a "single version of the truth." Companies
that partner with NCR to provide these general warehousing tools are BEZ Systems, Inc.
 Pine Cone Systems
 SAS Institute, Inc.
Dependent Data Marts
NCR maintains two notable partnerships for data-mart applications. NCR and Microsoft
have joined forces to provide data-mart and electronic commerce solutions. The
agreement is based on the integration of the NCR Teradata relational database
management system with Microsoft SQL Server technology. These two companies are Microsoft
 SAS Institute, Inc.
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Knowledge Discovery/Data Mining
These alliances provide NCR customers with tools for sifting through large amounts of
data to uncover meaningful correlations, patterns or trends. Data Mining, which is an
important step in the Knowledge Discovery process, can be analytical or interactive.
These companies include Angoss
 SPSS, Inc.
 Knowledge Discovery One (KD1)
 Quadstone
 SAS Institute, Inc.
 Torrent
Relational OLAP
Relational OLAP tool companies fall under the information access tools category.
Information access tool providers give end-users the ability to access data, turn the data
into usable information, and therefore enhance the decision-making process for NCR data
warehouse products. ROLAPs provide multi-dimensional analysis capabilities but without
the requirement to build a secondary data store. These are Information Advantage
 MicroStrategy, Inc.
 PLATINUM Technology
Client OLAP / Query & Reporting
These providers also add information access tools to NCR’s offerings. With such tools, no
new application or report needs to be developed. Rather, the user is free to follow a train
of thought, pose any query, and explore the information held in the database. These
alliances include Hummingbird Communications Ltd.
 Brio Technology
 Business Objects
 Cognos
 Information Builders
 PLATINUM Technology
 SAS Institute, Inc.
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Strategies
NCR’s products and strategic alliances complement their organizational strategies. To get
a clearer idea of the direction and focus of the company it is important to examine these
strategies. NCR’s two most current and defining organizational strategies emphasize
customer privacy and specialized industry solutions.
Customer privacy is a very recent initiative that the company has rallied around. NCR is
putting together a strategy to help businesses understand who their customers are and
how best to serve them. NCR claims to be the first solutions firm to place customer privacy
at the center of its strategy (The first company to apply the principles of consumer data
protection to its data warehousing solutions.). "We've seen the growing emergence of
consumer-data privacy regulations coming from both the European Union and in [the U.S.]
Congress," says Bob Henderson, NCR’s spokesman on privacy, "And we want to make
sure our customers will be in compliance with any general regulations and emerging
standards." NCR is taking a different approach than its competitors are taking by
connecting those capabilities to the database server itself. Vendors usually separate how
the database is used from how the database engine works. But NCR doesn't do that. New
database products from NCR will enable marketers to add a customer's personal
preference on how their data should be used. The idea is to ensure the level of marketing
is adapted to each consumer.
NCR also builds industry-specific and horizontal data warehousing solutions for virtually
any industry application including retail, financial, communications, consumer goods
manufacturing, insurance, transportation and government. They offer
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specialized solutions for retail, financial and communications industries in particular. These
elaborate strategies have evolved into three tailored solutions – Neighborhood Retailing
(retail solutions), Customer Management Solutions (financial solutions) and Customer
Relationship Management (communications solutions).
Neighborhood Retailing
Neighborhood Retailing allows retailers to manage each customer, product or outlet as an
"entity of one." NCR’s High Performance Merchandising and Marketing solutions
consolidate and analyze transaction data to determine trends, buyer preferences and
product sales. The mission of High Performance Merchandising and Marketing (HPM&M)
is centered around the implementation of solutions to effectively solve Retail Business
issues through the use of detailed data in a scalable enterprise data warehouse
environment. NCR’s Neighborhood Retailing defines how retailers can better use
information to understand customers and service them profitably. NCR provides this
information (detailed business data) through the implementation of a complete, end-to-end
business solution.
Initially, data warehouse solutions focused on the analysis of historical merchandise data.
Today, HPM&M extends the ability to analyze the growing availability of information about
merchandise and customers – including in-house credit cards, loyalty and frequent
shopper programs. Analysis of shopping behavior not only makes it possible to more
precisely "tune" a store’s offering to its target market, but to also influence demand on a
consumer-specific basis.
NCR applies its core competencies in data warehousing technology and HPM&M
business solutions to support three main goals. First, to improve the consistency, quality
and usefulness of information in support of the merchandising function. Second, to
combine this merchandising information with consumer purchasing information to improve
the precision and effectiveness of the marketing function. Third, to provide the means for
retailers to focus their merchandising and marketing information on enriching each
customer’s shopping experience.
Customer Management Solutions
Customer Management Solutions (CMS) is dedicated to assisting financial services
organizations exploit data to help change the way they interact with and manage their
customers. By turning data into actionable knowledge, banks can address issues in sales
and marketing such as customer retention, behavior segmentation, issues of risk
management and customer profitability and channel management.
CMS also focuses on “Relationship Engineering” to understand customers and uses a
logical data model that enables the financial organization and its database to talk. NCR
also uses a set of business value models that add value to the operation by enabling
organizations to engineer real relationships with its customers. These models include:
Value Analyzer- software that tells a company the hard facts of what individual customer
relationships are worth to the bottom line and why they are valuable as well.
Behavior Explore- analyzes customer behavior to answer the question why? Why should
a particular customer be offered that product, through that channel at that location? What
products and channels are they likely to need in the future?
Relationship Optimizer- a dynamic marketing and communications application that gives
the company the capability to optimize its customer contacts and delivery channels: not
just once a month but thousands of times a day.
NCR also develops software called InterRelate+ that enables communication through all
key channels – branch, Internet and call center – in a way that gives customers the choice
of how and when they interact with the company. Using InterRelate+ channels can be
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easily integrated, giving companies a single, 360-degree view of the customer across all
channels. At the same time, InterRelate+ offers customers a single, consistent experience
of a company’s brand.
Customer Relationship Management
NCR Customer Relationship Management helps communications companies understand
and act on the value of each customer by providing a set of integrated business solutions
that targets and manages customer segments and products within the communications
industry. In today's Communications Industry acquiring customers, retaining customers,
and building customer loyalty are imperative. NCR markets to communication services
providers with their Scalable Data Warehouse solutions that aim to turn customer
information into competitive advantage.
The NCR Yield Management Program consists of a portfolio of focused business solutions
aimed at solving business problems associated with identifying and growing the "best"
customers, such as customer retention, profitability analysis and campaign management.
NCR’s Network Infrastructure Warehouse is a family of solutions that will directly support
decision-making in the areas of network capacity, inventory, maintenance and provisioning
to realize cost savings and increase revenue for communications service providers. NCR
SmartEC family of solutions helps communications companies extend their services to
their customers via corporate Intranet/Extranet, to include Internet Billing and Customer
Care. The Public Electronic Commerce Kiosk enables a low-cost, high-impact alternative
channel, which will extend the reach of the wireless carrier from in-store, to third party
dealers, or to remote locations.
NCR Customers
NCR is putting its relationships and strategies with retailers, financial institutions, and other
companies to work by offering its world leading data warehousing system. Retailers such
as Hallmark, Sears, and Wal-Mart use NCR's data warehousing to analyze their
profitability on a product, customer, and store-level basis. Wal-Mart now runs each store
independently of all the others. This means replenishment at the store level and precise
information to its buyers and suppliers. Wal-Mart also analyzes seasonal buying trends,
make discounting decisions, and react to merchandise volume and movement at any time.
In nonretail industries, banks use NCR's data warehousing to separate the profitable
customers from the freeloaders. Airlines use data warehousing to track frequent fliers and
revenue-maximizing routes. Telecommunications companies can better track customers'
needs, calling patterns, and profit-maximizing pricing.
NCR is leading efforts to develop new products to help its customers leverage themselves
with technology. For example, in supermarkets, NCR is working on an automated pricing
system for every item in the store. NCR's point-of-sale machines let retailers instantly
update inventory and process sales much more efficiently. The U.S. Postal Service hired
NCR to install point of-sale terminals in 10,000 post offices. The remaining 50,000 post
offices to be automated are up for bid, and NCR is in a commanding position to win this
business.
In the communications industry, NCR provides much needed information management
and the ability to bring new products to market quickly. For example, when NCR customer
SNET introduced its caller ID service, marketing users accessed the data
warehouse to identify the customer segments that were most likely to purchase the
product. SNET then targeted these customers through direct mail and telemarketing.
AT&T Wireless plans to use the NCR data warehouse with the NCR Teradata RDBMS to
build better customer profile information for improving service to existing customers and
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enhancing its direct marketing capabilities. AT&T will also use the data warehouse to find
better ways to manage customer retention and reduce churn through predictive modeling,
and to improve customer prospecting. Quick response times are imperative in today’s
expanding communications market.
NCR customers and data warehouses are not confined to the United States either.
Japan’s second largest travel agency, Kinki Nippon Tourist, relies on NCR Teradata
database to implement ‘one-to-one’ marketing strategies to tailor travel ads to customers.
The British Audit Commission selected NCR and Synectics Solutions to provide
nationwide data matching solution to identify fraudulent benefit claims. Zurich Kemper Life,
formed by the acquisition of the Swiss-based Zurich Group and Kemper Corporation,
turned to NCR to help build a data warehouse to pull data from its disparate data sources
and give the company an enterprise view of its operations. The NCR data warehouse and
its sales reporting applications provide users access to reliable, timely data which helps
shorten the company's forecasting cycle, providing a significant competitive advantage.
NCR must compete for its business with just about anyone who makes and peddles
software. Databases from Oracle, IBM and Microsoft are quickly adding all the features
that perform sophisticated requests on multiterabyte data-warehouses. Their systems will
do this work along with payroll, shipping and accounting. The fact that NCR was cloistered
away under AT&T's ownership from 1991 to 1996, and has had five different CEOs, hasn't
helped the company's reputation.
Being much bigger than NCR, many of these software outfits can easily outgun it when it
comes to recruiting software talent. Oracle, for instance, has three times as many software
developers working on database tools as NCR does.
Conclusion
NCR Corporation is currently number one in automated teller machines and number two
in cash registers and scanners. However, they are now dedicated to becoming the leader
in data warehousing. Even if it means pouring profits from ATM’s and cash registers into
their data warehouse division. They also plan on strong marketing and acquisitions to
boost their data warehouse business.
However, NCR’s core business in older computer systems is declining by almost 30% a
year, which is much faster than predicted. Data warehouse sales have yet to pick up this
slack. Another concern is NCR's reliance on international markets for 60% of its revenue.
Management says the AsiaPacific region, which represents nearly 20% of revenue, is
near the bottom. Its stock price has dropped nearly 50% over the last four months. The
decline of their PC and low-end server products will hinder revenue growth for awhile as
well.
NCR faces competition from Andersen Consulting, EDS, IBM, and Unisys, among others.
It still trails Oracle, Compaq Computer, IBM and Hewlett-Packard in data warehouse
sales. But, NCR says a focus on its core industries gives it an advantage over its
competitors, which may not have NCR's expertise in these select industries.
Near the end of the AT&T era in 1996, NCR CEO Lars Nyberg realized that NCR couldn't
continue to exist selling hardware, but could become profitable again by capitalizing on its
112 years of strong relationships with retailers and the financial industry. So, their focus is
on putting together a solid strategy to help businesses understand who their customers
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are and how best to serve them. NCR has dramatically scaled back its PCs and low-end
server offerings and eliminated huge layers of overhead. It now outsources to Solectron
nearly everything it used to manufacture itself, resulting in great cost savings. Giga
Information Group analyst Lou Agosta recently rated NCR the technological leader in
providing large data warehouses.
With this outlook, NCR is also poised to begin acquiring companies. It holds large
amounts of cash and very little debt. CEO Nyberg forecasts six to ten acquisitions in the
$20 million to $100 million range in the near future. This will help NCR expand its portfolio
of software, move into new industries and add new talent.
The outlook for NCR is very bright, provided that ER Modeling continues to be a popular
form of database design. They have the technology and assets in place to both lead and
define the data warehousing industry for years to come. NCR’s data warehousing skills
will be important as e-commerce grows, because Web sites collect large volumes of data
whenever browsers visit or purchases are made. And as e-commerce and data
warehousing continue to converge in the future and companies look to track customers,
NCR will be there to provide solutions.
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References
Bulkeley, William M., NCR Wants to Be the Leader In Data-Warehousing Market, The Wall Street Journal, Dow
Jones and Company Inc., October 14, 1999.
Data Warehouse Design Solutions, Paul Gray and Hugh. Prentice Hall Publishing, 1998.
http://www.data-warehouse.com/articles/
http://www.data-warehouse.com/resource/articles
http://www.ncr.com/sdw
http://rd.runnet.ru/is/dmreview.com/issues/1998/may/articles/may98/56.htm
http://dmreview.com/editorial/dmreview
http://www3.ncr.com/product/data_warehouse/success.html
http://www3.ncr.com/product/data_warehouse/papers.html
Introduction to Teradata for Windows NT, Teradata Warehouse Solutions Online Documentation,
http://www.info.ncr.com/sd/index2.htm
NCR Scalable Data Warehousing CD-ROM.
NCR Teradata Overview, http://www3.ncr.com/product/brochures/teradata.htm
NCR Teradata for Windows NT Demo CD-ROM.
NCR Teradata RDBMS, http://www3.ncr.com/product/teradata/product.html.
Schaff, William, NCR’s Retooling Registers, Informationweek, CMP Media Inc., November 30, 1998.
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