Microsoft 70-458

Free Questions in OTE format

About Microsoft 70-458 dump

This exam is intended for candidates who have already earned any one of the MCTS certifications on SQL Server 2008, have completed Exam 457, and who wish to transition their skills to MCSA: SQL Server 2012.

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