Pass 70-463 MCSA Certification Exam Fast
70-463 Exam Has Been Retired
This exam has been replaced by Microsoft with new exam.
Microsoft 70-463 Exam Details
The Microsoft 70-463 test is associated with the creation of BI solutions. It prepares those eager to build skills in data cleansing, implementing data warehouses, and extracting, transforming as well as loading data with SQL Server 2012/2014.
Exam 70-463 is proposed for data warehouse developers and those candidates who can extract, transform, and load data. As a rule, these are individuals aspiring for the MCSA: SQL Server 2012/2014 certificate of the associate level.
To opt for this exam no prerequisites are demanded, but one must have passed 70-461 and 70-462 exams earlier. Also, those with the plan to take 70-463 ought to go into the details of the exam topics to obtain a thorough comprehension of them.
This test is to be held in languages like English, Portuguese (Brazil), Chinese (Simplified), Japanese, German, and French. Itâ€™s to have 40-60 questions which you should cover in 2 hours. Styles mainly include MCQs but active screen, build lists, short answer, review screen, short answer, and others are likely to be present in the final exam too. Success in such a test implies that one has achieved points starting from 700. The whole process goes for $165 as an entry fee.
The topics below are responsible for your success in the Microsoft 70-463 test and the achievement of the MCSA: SQL Server 2012/2014 qualification:
- Designing and Implementing a Data Warehouse;
- Configuring and Deploying SSIS Solutions;
- Data Extraction and Transformation;
- Loading Data;
- Building Solutions for Data Quality.
To draw abilities from each tested area, candidates must consider all the knowledge scopes presented. The Designing and Implementing a Data Warehouse topic starts with designing and implementing dimensions, which includes outlining shared or conformed dimensions, determining if one needs support for slowly transforming dimensions, describing attributes, designing hierarchies, checking if one needs snowflake or star schema, and determining the granularity of relationship with fact tables. Other covered fields are defining keys such as business transactional or surrogate/oneâ€™s own data warehouse, determining the need for lineage or auditing, implementing dimensions, and executing data lineage associated with dimension tables. In addition, such a segment extends to designing and implementing fact tables. This considers building a data warehouse that is in support of many to many relationships, properly indexing fact tables, utilizing columnstore indexes, additive measures, partitioning, semi-additive measures, and putting into operation fact tables. Other tasks considered here are non-additive measures, implementing data lineage of fact tables, determining the loading method to employ in fact tables, and designing summary tables for aggregation.
The second topic on Configuring and Deploying Solutions for SSIS covers up to five sections. The first one is about troubleshooting issues to do with data integration such as performance, execution or transformation failed, troubleshooting failed packages, connectivity breaches, data viewers, and batch cleanup. The second objective touches on the installation and maintenance of SSIS components, where the focus is on software executions, development box & server, implementing specifics for executing remote packages, how to plan for installation (32 versus 64 bit), upgrading, provisioning of accounts, and catalog creation. In the third part, you will find out about the implementation of auditing, logging, and event handling. Some of the areas highlighted here scrutinize executing the audit package, propagating events, using Event Handlers, and implementing custom logging. In the fourth part of this topic, you will be dealing with deploying SSIS solutions. This captures the creation and configuration of SSIS catalog, deploying SSIS packages, validating deployed packages, deploying SSIS packages, and more. The fifth sector regards configuring security settings for SSIS and includes the SSIS catalog database roles, protection levels for packages, and securing parameters for Integration Service.
The third objective looks at five distinct areas. The first one is centered on defining connection managers and covers planning connection managers configuration, project level or packaging level manager, defining connection strings, and connection strings parameterization. The second field extends to designing data flow, which looks at defining data destinations and sources, distinguishing non-blocking and blocking transformations, using varied methods in pulling out changed data coming from data sources, determining proper components for data flow, checking if to use SSIS lookup, SQL Joins, or merge join transformations, batch processing versus row by row processing, and more. The third area regards implementing data flow. This delves into debugging data flow, using the proper components for data flow, SQL/SSIS data transformation, mapping identities with the use of SSIS fuzzy lookup, specifying data sources and their destinations, transforming and loading data, maintaining data integrity, etc. The fourth portion is about managing the execution of SSIS packages. Some of the matters it addresses are scheduling a package implementation with the use of SQL Server Agent, executing packages with the use of DTEXEC, putting into operation package execution, using DTEXECUI, ETL restartability, and taking advantage of PowerShell in executing scripts. The fifth subtopic touches on the implementation of script tasks in SSIS. Itâ€™s about determining if itâ€™s proper to utilize script tasks, extend the capacity of control flow, and perform custom actions as required during control flows.
The fourth field discusses varied tasks related to data loading. In particular, it captures designing control flows with tasks like determining a control flow, checking the needed tasks and containers, regulating precedence constraints, staging and transaction control, designing an SSIS package strategy, determining event handlers, and conditioning security needs, among others. It also details implementing package logic with the use of SSIS parameters and variables. Issues to handle here involve user variables, variable scope, data types, configuring packages, parent package variables, property expressions, and more. Another section captured within such a domain is about implementing a control flow. It handles checkpoints, debugging control flows, data profiling, the creation of package templates, managing transactions in SSIS, monitoring parallelism, and others. There is also the sector on implementing options of data loading, which looks at full & incremental loading strategy for data, planning for loads into indexed tables, configuring proper bulk loading options, etc. This domain ends with the section about implementing script models. Tasks highlighted here are creating SSIS packages that handle SCD Type 2 changes without utilizing the SCD component, destination, source, and transformation component and using cases like an error message.
The final topic concerning Building of Quality Solutions for Data captures the installation and maintenance of quality services for data. Issues covered in this part detail installation prerequisites, adding users, .msi package, and identity analysis such as data governance. It also concerns the implementation of master data management solutions. This covers the installation of Master Data Services (MDS), implementing MDS, creating entities, models, collections, attributes, hierarchies, defining security roles, and importing/exporting subscriptions. The final bit dives deeper into the creation of a data quality project for cleaning data. This includes profiling Online Transaction Processing (OLTP) & other source systems, creating data quality projects, the management of data quality knowledge base, using data quality client, managing data cleansing/quality, handling history & data quality, improving data quality, and mapping & deduplication of identity.
Career Prospects, Job Positions, and Salary
As BI continues to gain momentum, most organizations rely on relational databases. This is to shape the most vital decisions regarding their businesses. With the MCSA and the skills in the implementation of a data warehouse, you will be leading the way in creating and availing complex solutions for managing data. Some positions that befit your skills include a BI developer, ETL developer, data engineer, data analyst, and database administrator. As PayScale.com specifies, those holding such positions should expect compensation of around $71k in one year.
Career Path: Which Certification after MCSA?
If you achieve your MCSA: SQL Server 2012/2014 validation before its expiry date of 31st January 2021, the expert-level MCSE: Data Management and Analytics would be a great certificate to take on next.