Introduction
This is top class certification exam of Microsoft. It is designed by group of Microsoft advanced level official certification experts. It has covered all the aspects of depth in the technical questions and delivery methodology of official Microsoft certification by following the complete exam syllabus. This certification questions will give you the most realistic experience in the real world exam.
Exam Details:
This Exam contains multiple choices, multi selection and true or false questions.
Exam Time Limit: 90 Minutes
Exam Syllabus:
Design and implement a data
warehouse (10–15%)
- Design
and implement dimensions
·
Design shared/conformed dimensions; determine if 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; determining the loading method for the fact tables; implement data
lineage of a fact table; design summary aggregation tables
Extract and transform data (20–25%)
- Define
connection managers
·
Plan the configuration of connection managers; package level or
project level connection manager; define a connection string; parameterization
of connection strings
- 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 versus 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 custom data sources, destinations, and transforms;
determine what to do with erroneous rows; determine auditing needs;
trusted/authoritative data sources, including warehouse metadata; extracting only
changed rows
- 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
(advanced); 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
- Manage
SSIS package execution
·
Schedule package execution by using SQL Server Agent; execute
packages by using DTEXEC; execute packages by using SQL Server Management
Studio; implement package execution; plan and design package execution
strategy; use PowerShell to execute script; monitor the execution using
Management Studio; use DTEXECUI; ETL restartability
- Implement
script tasks in SSIS
·
Determine if it is appropriate to use a script task; extending the
capability of a control flow; perform a custom action as needed (not on every
row) during a control flow
Load data (25–30%)
- Design
control flow
·
Determine control flow; determine containers and tasks 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; using variables in precedence
constraints; referring to SSIS system variables; design dynamic SSIS packages;
package configurations (file or SQL tables); expressions; package and project
parameters; project level connection managers; variables; 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; managing parallelism; using
precedence constraint to control task execution sequence; creating package
templates; using 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; plan for loads into indexed
tables; configure appropriate bulk load options; select an appropriate load
technique (SSIS Destination versus T-SQL) and load partitioned tables
- Implement
script components in SSIS
·
Create an SSIS package that handles SCD Type 2 changes without
using the SCD component; work with script component in SSIS; deciding when it
is appropriate to use a script component versus a built in; source,
transformation, destination component; use cases: web service source and
destination, getting the error message
Configure and
deploy SSIS solutions (20–25%)
- 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
- Install
and maintain SSIS components
·
Software installation (IS, management tools); development box and
server; install specifics for remote package execution; planning for
installation (32- versus 64-bit); upgrade; provisioning the accounts; creating
the catalog
- 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; how
to install custom components and tasks; deploy SSIS packages by using DTUTIL
- Configure
SSIS security settings
·
SSIS catalog database roles; package protection levels; secure
Integration Services packages that are deployed at the file system; secure
Integration Services parameters, configuration
Build data quality
solutions (15–20%)
- Install
and maintain data quality services
·
Installation prerequisites; .msi package; adding 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, 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 data quality project;
use data quality client; improve data quality; identity mapping and
deduplicating; handle history and data quality; manage data quality/cleansing
How this exam is useful to you?
This exam is intended for the people who are preparing for the 70-463 Implementing a Data Warehouse with Microsoft SQL Server 2012-2014 Certification. This exam is prepared exclusively as per the real certification exam. This will definitely help to check your skills before attempting the main exam. Also it will give the complete idea how main exam will be.
This exam will evaluate your skills and will give you report on how far you are skillful in 70-463 Implementing a Data Warehouse with Microsoft SQL Server 2012-2014 certification exam.
In case you face any issues during the exam or you have any queries, email us at [email protected]
Wish you all the best for your certification exam and we are always ready to help you to get certified and grow in your career.
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Exam Details:
This Exam contains multiple choices, multi selection and true or false questions.
Exam Time Limit: 90 Minutes
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