Learn Teradata in 30 days

Teradata Basics

Teradata Product Overview
Processing Types and Characteristics
Data Warehouse Architectures
Relational Database Concepts
Teradata RDBMS Components and Architecture
 Database Managed Storage
 Data Access Mechanics
 Data Availability Features
 Teradata Tools and Utilities
 Workload Management
 Security and Privacy

Teradata SQL

 Teradata Extensions
 Data Definition Language (DDL)
 Data Manipulation Language (DML)
 Data Control Language (DCL)
 Views and Macros
 Logical and Conditional Expressions
 Data Conversions and Computations
 CASE Expressions
 Subqueries and Correlated Subqueries
 Joins
 Attribute and String Functions
 Set Operations
 Analytical Functions
 Time/Date/Timestamp/Intervals (ANSI vs. TERADATA)
 Stored Procedures Concepts
 Aggregations
 SQL Optimization Concepts
 Advanced SQL Concepts

Teradata Physical Design and Implementation

 Physical Database Design Overview
Table Attributes table types
 Column Attributes – Data types
Statistics
Primary Indexes – Advantages of Partitioned primary index
Secondary Indexes – Comparison of primary and secondary indexes
 Other Index Considerations
 Transaction Isolation
 Physical Database Operations
 Teradata Query Analysis
Database (Spool/Perm) Space Management

Teradata 12 Database Administration

 System Software Setup and Parameters
 User and Security Management
 Session Management
 Load and Extract
 System Administration Tools
 System Workload Analysis and Management
 Performance Optimization
 Capacity Management and Planning
 Business Continuity
 Object Maintenance

Teradata Solutions Development

 The solutions development process: data integration and access, performance analysis tools, and data model characteristics
 Solutions development considerations: physical design, data integration, data access performance, partitioning, security, privacy, and APIs.
 The solutions development planning process: capacity, security, and data warehouse administration planning, and analyzing solution performance metrics
 Solutions development strategies: advanced SQL functions, table selection, transaction mode, coding constructs, transaction types, NULL processing, and recursive queries
 Data integration strategies: load utilities, export options, load strategies, referential integrity, and locking.
 Solutions optimization: performance improvement, statistics collection, secondary and join indexes, understanding EXPLAINs, and Load utility performance.

 Basics
o centrally located architectures vs. physically distributed architectures, such as an appliance
o star schema vs. third normal form
o non-partitioned vs. single level vs. multi-level partitioned tables
o benefits of PPI, MLPPI
o benefits of join indexes
o node failover
 SQL
o ANSI vs. Teradata mode in the areas of transaction protocol, defaults, conversions, and table creation
o use of aliasing in table joins
o evaluation order of various join types
o joining partitioned tables
o formatting options for internationalization of data types
o UNION vs. UNION ALL
o Window Aggregate functions
o use of Timestamp in expressions
o use of Intervals in expressions
o extended GROUP BY operators
o TOP N vs. SAMPLE
o effect of dropping or altering a partition
o use of CREATE TABLE AS
o correctly written SELECT statement
o use of ANSI MERGE INTO and UPDATE (upsert processing)
o change a user’s role
o use a locking modifier in a view or macro
o IN and NOT IN logical predicate
o explicit and implicit data type conversion
o SQL statement for a correlated subquery
o use of a derived table
 Physical Design and Implementation
o interpret DBQL output
o determine columns for compression – Introduction to compresssion
o ALTER a table vs. CREATE a new table
o use ALTER table on PPI tables
o tuning options that minimize table fragmentation
o performance considerations of Referential Integrity
o converting a UNICODE value to Latin
o identify columns for statistics collection

o when does Random AMP sampling occur

o when to use multi-column statistics
o when to use PPIs and MLPPIs
o when to use NUSIs
o when to use STJIs and Multi-table Join Indexes
o conflicting locks in a multi-statement request
o explain partial value searches and data conversions on index utilization
o identify if skew on processing will occur
 Database Administration
o ctl/xctl functionality
o identify the outcome of partition maintenance
o recovery implications of user defined functions, table functions, user defined types, and stored procedures
o actions taken using object use count
o granting access rights
o use of Roles in relation to security management
o use of Profiles
o steps to solve session management problems
o identify use in a shared userid scenario
o unique features of Teradata Parallel Transporter
o how to control utility limits
o tools/resources to determine the cause of system bottleneck
o ResUsage tables to use for problem identification
o Priority Scheduler relative weights
o distinguish between Teradata Dynamic Workload Manager (TDWM) features
o use of extrapolated and propagated statistics
o given a scenario, identify columns to collect statistics on
o characteristics of a well-performing tactical query
o potential solutions to capacity shortages
o features and functions of Online Archive
o features and functions of Partition Archive and Restore
 Solutions Development
o select an effective data integration approach based on application requirements
o select an effective data access approach based on differing application requirements
o contrast the update processes for event driven, active data warehouse, and BI environments, and identify their impact on development choices
o implement and manage application security and privacy
o impact of row and set manipulation requests on application performance and on developer choices
o correlate BI solution development choices with data access performance
o role of partitioning with respect to data integration
o behavior of an identity column
o resources to analyze solution performance metrics that can also be used during testing
o use of triggers
o recursive query performance issues
o compare Ordered Analytic Functions
o multi-statement request vs. multi-statement transaction

o identify the result of outer joins
o impact of NULL processing on a result set
o effect of Teradata Parallel Transporter parameters
o eliminate unwanted duplicate rows from a multi-set table
o locking impact caused by the different load utilities
o components for a dual system architecture
o describe the operation of a join plan
o use EXPLAIN to improve performance
o use Collect Statistics to improve performance
o use join indexes to improve performance
o given a scenario with table definitions, SQL, and data demographics, identify the best performing partitioning definition
 Enterprise Architecture
o use Teradata workload management to satisfy service level agreements
o capacity factors to consider prior to promoting an application into production
o given a scenario, determine the appropriate system hardware configuration
o given a scenario, identify the potential system and application availability characteristics including active data warehousing that can affect a database architecture
o options to improve slow-running query
o balance and reserve system resources for a heavily loaded system
o determine the inputs necessary to establish a query management and workload policy
o determine the effects of database optimization techniques including those on tables or indexes
o ETL vs. ELT design
o identify the appropriate approach for data movement
o use of surrogate keys
o use the LDM to design an integrated data architecture
o choose the appropriate indexes by converting a LDM to an Extended LDM
o methods to meet privacy requirements
o methods to meet user access auditing requirements
o benefits of data governance [on a growing enterprise data warehouse environment
o distinguish between in-database analytics, external processing, ROLAP technology, or External Cube technology
o optimization techniques for a high-volume tactical workload
o manage tactical workloads to meet SLAs
o effects of embedded (nested) views

 

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