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Actualkey Prepration Latest 70-458 : Transition Your MCTS on SQL Server 2008 to MCSA: SQL Server 2012, Part 2 Questions and Answers PDF's, Verified Answers via Experts - Pass Your Exam For Sure and instant Downloads - "Money Back Guarantee".
| Vendor | Microsoft |
| Certification | Microsoft Certified Professional |
| Exam Code | 70-458 |
| Title | Transition Your MCTS on SQL Server 2008 to MCSA: SQL Server 2012, Part 2 |
| No Of Questions | 300 |
| Last Updated | September 16,2024 |
| Product Type | Q & A with Explanation |
| Bundel Pack Included | PDF + Offline / Andriod Testing Engine and Simulator |
Exam 70-458
Transition Your MCTS on SQL Server 2008 to MCSA: SQL Server 2012, Part 2
Published: June 11, 2012
Languages: English, Japanese
Audiences: IT Professionals
Technology: Microsoft SQL Server 2012
Credit toward certification: MCP, MCSA, MCSE
Skills measured
This exam measures your ability to accomplish the technical tasks listed below. The percentages indicate the relative weight of each major topic area on the exam. The higher the percentage, the more questions you are likely to see on that content area on the exam. View video tutorials about the variety of question types on Microsoft exams.
Please note that the questions may test on, but will not be limited to, the topics described in the bulleted text.
Do you have feedback about the relevance of the skills measured on this exam? Please send Microsoft your comments. All feedback will be reviewed and incorporated as appropriate while still maintaining the validity and reliability of the certification process. Note that Microsoft will not respond directly to your feedback. We appreciate your input in ensuring the quality of the Microsoft Certification program.
If you have concerns about specific questions on this exam, please submit an exam challenge.
Manage data
Configure and maintain a backup strategy
Manage different backup models, including point in time recovery; protect customer data even if backup media is lost; perform backup/restore based on proper strategies including backup redundancy; recover from a corrupted drive; manage a multi-terabyte database; implement and test a database implementation and a backup strategy (multiple files for user database and tempdb, spreading database files, backup/restore); back up a SQL Server environment; back up system databases
Restore databases
Restore a database secured with TDE; recover data from a damaged DB; restore to a point in time; file group restore; page level restore
Implement and maintain indexes
Inspect physical characteristics of indexes and perform index maintenance; identify fragmented indexes; identify unused indexes; implement indexes; defrag/rebuild indexes; set up a maintenance strategy for indexes and statistics; optimize indexes (full, filter); statistics (full, filter) force or fix queue; when to rebuild vs. reorg and index; full text indexes; column store indexes
Import and export data
Transfer data; bulk copy; bulk insert
Implement security
Manage logins and server roles
Configure server security; secure the SQL Server using Windows Account/SQL Server accounts, server roles; create log in accounts; manage access to the server, SQL Server instance, and databases; create and maintain user-defined server roles; manage certificate logins
Manage database permissions
Configure database security; database level permissions; protect objects from being modified
Manage users and database roles
Create access to server/database with least privilege; manage security roles for users and administrators; create database user accounts; contained logins
Troubleshoot security
Manage certificates and keys; endpoints
Implement high availability
Implement AlwaysOn
Implement a mirroring solution using AlwaysOn; failover
Implement database mirroring
Set up mirroring; monitor the performance of database mirroring
Implement replication
Troubleshoot replication problems; identify appropriate replication strategy
Design and implement a data warehouse
Design and implement dimensions
Design shared/conformed dimensions; determine whether you need support for slowly changing dimensions; determine attributes; design hierarchies; determine whether you need star or snowflake schema; determine the granularity of relationship with fact tables; determine the need for auditing or lineage; determine keys (business transactional or your own data warehouse/surrogate keys); implement dimensions; implement data lineage of a dimension table
Design and implement fact tables
Design a data warehouse that supports many to many relationships; appropriately index a fact table using columnstore indexes; partitioning; additive measures; semi-additive measures; non-additive measures; implement fact tables; determine the loading method for the fact tables; implement data lineage of a fact table; design summary aggregation tables
Extract and transform data
Design data flow
Define data sources and destinations; distinguish blocking and non-blocking transformations; use different methods to pull out changed data from data sources; determine appropriate data flow components; determine the need for supporting Slowly Changing Dimensions (SCD); determine whether to use SQL Joins or SSIS lookup or merge join transformations; batch processing vs. row by row processing; determine the appropriate transform to use for a specific task; determine the need and method for identity mapping and deduplicating; fuzzy lookup, fuzzy grouping, and Data Quality Services (DQS) transformation; determine the need for text mining; determine the need for custom data sources, destinations, and transforms; determine what to do with erroneous rows; determine auditing needs; determine sampling needs for data mining; trusted/authoritative data sources, including warehouse metadata
Implement data flow
Debug data flow; use the appropriate data flow components; SQL/SSIS data transformation; create SSIS packages that support slowly changing dimensions; use the Lookup task in SSIS; map identities using SSIS Fuzzy Lookup; specify a data source and destination; use data flows; different categories of transformations; read, transform, and load data; understand which transforms to use to accomplish a specific business task; data correction transformation; performance tune an SSIS dataflow; optimize Integration Services packages for speed of execution; maintain data integrity, including good data flow
Implement script tasks in SSIS
Determine whether it is appropriate to use a script task; extend the capability of a control flow; perform a custom action as needed (not on every row) during a control flow
Load data
Design control flow
Determine control flow; determine containers and tasks that are needed; determine precedence constraints; design an SSIS package strategy with rollback, staging, and transaction control; decide between one package or multiple packages; determine event handlers; determine variables; determine parameters on package and project level; determine connection managers and whether they are package or project level; determine the need for custom tasks; determine how much information you need to log from a package; determine the need for checkpoints; determine security needs
Implement package logic by using SSIS variables and parameters
User variables; variable scope, data type; implement parameterization of properties using variables; use variables in precedence constraints; refer to SSIS system variables; design dynamic SSIS packages; package configurations (file or SQL tables); expressions; package and project parameters; project level connection managers; implement dynamic package behavior; configure packages in SSIS for different environments, package configurations (xmlconfiguration file, SQLServer table, registry entry; parent package variables, environment variable); parameters (package and project level); project connection managers; property expressions (use expressions for connection managers)
Implement control flow
Checkpoints; debug control flow; implement the appropriate control flow task to solve a problem; data profiling; use sequence containers and loop containers; manage transactions in SSIS packages; manage parallelism; use precedence constraint to control task execution sequence; create package templates; use the execute package task
Implement data load options
Implement a full and incremental data load strategy; plan for an incremental update of the relational Data Mart
Configure and deploy SSIS solutions
Troubleshoot data integration issues
Performance issues; connectivity issues; execution of a task or transformation failed; logic issues; demonstrate awareness of the new SSIS logging infrastructure; troubleshoot a failed package execution to determine the root cause of failure; troubleshoot SSIS package failure from an invalid datatype; implement break points; data viewers; profile data with different tools; batch cleanup
Implement auditing, logging, and event handling
Audit package execution by using system variables; propagate events; use log providers; log an SSIS execution; create alerting and notification mechanisms; use Event Handlers in SSIS to track ETL events and errors; implement custom logging
Deploy SSIS solutions
Create and configure an SSIS catalog; deploy SSIS packages by using the deployment utility; deploy SSIS packages to SQL or file system locations; validate deployed packages; deploy packages on multiple servers; install custom components and tasks; deploy SSIS packages by using DTUTIL
Build Data Quality solutions
Install and maintain Data Quality Services
Installation prerequisites; use Data Quality Server Installer; add users to the DQ roles; identity analysis, including data governance
Implement master data management solutions
Install Master Data Services (MDS); implement MDS; create models, entities, hierarchies, collections, and attributes; define security roles; import/export; subscriptions
Create a data quality project to clean data
Profile Online Transaction Processing (OLTP) and other source systems; data quality knowledge base management; create a data quality project; use Data Quality Client; improve data quality; identity mapping and deduplicating; handle history and data quality; manage data quality/cleansing
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