data and analytics

1. Teradata Product Overview
After completing this module, you will be able to:
• Describe the purpose of the Teradata product
• Give a brief history of the product
• List major architectural features of the product

2. What is Teradata?
Teradata is a Relational Database Management System (RDBMS).
Designed to run the world’s largest commercial databases.
• Preferred solution for enterprise data warehousing
• Executes on UNIX MP-RAS and Windows 2000 operating systems
• Compliant with ANSI industry standards
• Runs on a single or multiple nodes
• Acts as a “database server” to client applications throughout the enterprise
• Uses parallelism to manage “terabytes” of data
• Capable of supporting many concurrent users from various client platforms (over a
TCP/IP or IBM channel connection).
Win XP
Win 2000
UNIX
Client
Mainframe
Client
Teradata
DATABASE

3. Teradata – A Brief History
1979 – Teradata Corp founded in Los Angeles, California
– Development begins on a massively parallel computer
1982 – YNET technology is patented
1984 – Teradata markets the first database computer DBC/1012
– First system purchased by Wells Fargo Bank of Cal.
– Total revenue for year - $3 million
1987 – First public offering of stock
1989 – Teradata and NCR partner on next generation of DBC
1991 – NCR Corporation is acquired by AT&T
– Teradata revenues at $280 million
1992 – Teradata is merged into NCR
1996 – AT&T spins off NCR Corp. with Teradata product
1997 – Teradata database becomes industry leader in data warehousing
2000 – 100+ Terabyte system in production
2002 – Teradata V2R5 released 12/2002; major release including features such as PPI,
roles and profiles, multi-value compression, and more.
2003 – Teradata V2R5.1 released 12/2003; includes UDFs, BLOBs, CLOBs, and more.

4. How Large is a Trillion?
1 Kilobyte = 103 = 1000 bytes
1 Megabyte = 106 = 1,000,000 bytes
1 Gigabyte = 109 = 1,000,000,000 bytes
1 Terabyte = 1012 = 1,000,000,000,000 bytes
1 Petabyte = 1015 = 1,000,000,000,000,000 bytes
1 million seconds = 11.57 days
1 billion seconds = 31.6 years
1 trillion seconds = 31,688 years
1 million inches = 15.7 miles
1 trillion inches = 15,700,000 miles (30 roundtrips to the moon)
1 million square inches = .16 acres = .0002 square miles
1 trillion square inches = 249 square miles (larger than Singapore)
$1 million = < $ .01 for every person in U.S.
$1 billion = $ 3.64 for every person is U.S.
$1 trillion = $ 3,636 for every person in U.S.

5. Designed for Today’s Business
Teradata’s Charter meets the business needs of today
and tomorrow with:
• Relational database – standard for database design
• Enormous capacity – billions of rows, terabytes of
data
• High performance parallel processing
• Single database server for multiple clients – “Single
Version of the Truth”
• Network and mainframe connectivity
• Industry standard access language – Structured
Query Language (SQL)
• Manageable growth via modularity
• Fault tolerance at all levels of hardware and
software
• Data integrity and reliability

6. Teradata’s Competitive Advantages
• Unlimited, Proven Scalability – amount of data and number of users; allows
for an enterprise wide model of the data.
• Unlimited Parallelism – parallel access, sorts, and aggregations.
• Mature Optimizer – handles complex queries, up to 64 joins per query, ad-hoc
processing.
• Models the Business – 3NF, robust view processing, & provides star schema
capabilities.
• Provides a “single version of the truth”.
• Low TCO (Total Cost of Ownership) – ease of setup, maintenance, &
administration; no re-orgs, lowest disk to data ratio, and robust expansion
utility (reconfig).
• High Availability – no single point of failure.
• Parallel Load and Unload utilities – robust, parallel, and scalable load and
unload utilities such as FastLoad, MultiLoad, TPump, and FastExport.

7. Teradata Manageability
Things a Teradata DBA never has to do!
• Reorganize data or index space
• Pre-allocate table/index space, format partitions
• Pre-prepare data for loading (convert, sort, split, etc.)
• Ensure that queries run in parallel
• Unload/reload data spaces due to expansion
• Design, implement and support partition schemes.
• Write or run programs to split the input source files into partitions for
loading
A DBA knows that if the data doubles, the system can
expand easily to accommodate it.
The command and workload for creating a table that will
have 100,000 rows is the same as creating a table that will
have 1,000,000,000 rows!