Microsoft 70-413 IT Certification Dumps

Microsoft 70-413 tutorials and download Designing and Implementing a Server Infrastructure exam details with real questions and answers.

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Data Loading
08.12.13 (10:39 pm)   [edit]
Data Loading

Two distinct groups of tasks form the data loading function. When you complete the design and construction of the data warehouse and go live for the first time, you do the initial loading of the data into the data warehouse storage. The initial load moves large volumes of data using up substantial amounts of time. As the data warehouse starts functioning you continue to extract the changes to the source data, transform the data revisions, and feed the incremental data revisions on an on-going basis. Figure 2-7 illustrates the common types of data movements from the staging area t the data ware-house storage'.

Data Storage Component

The data storage for the data warehouse is a separate repository. The operational systems of your enterprise support the day-to-day operations. These are online transaction processing applications. The data repositories for the operational systems typically contain only the current data. Also, these data repositories contain the data structured in highly normalized formats for fast and efficient processing. ln contrast, in the data repository for a data warehouse, you need to keep large volumes of historical data for analysis. Further, you have to keep the data in the data warehouse in structures suitable for analysis, and not for quick retrieval of individual pieces of information.

Therefore, the data storage for the data warehouse is kept separate from the data storage for operational systems. An in your databases supporting operational systems, the updates to data happen as transactions occur. These transactions hit the databases in a random fashion. I low and when and the transactions change the data in the databases is not completely within your control. The data 70-413 pass4sure in the operational databases could change from moment to moment. When your rent analysts use the data in the data warehouse for analysis, they need to know that the data is stable and that it represents snapshots at specified periods.

  • This function is time-consuming
  • Initial load moves very large volume of data
  • The business conditions determine the refresh cycles

As they are working with the data, the data storage must not be in a state of continual updating. For this reason, the data warehouses are "read-only" data repositories. Generally, the database in your data warehouse must be open. Depending on your requirements you are likely to use tools from multiple vendors. The data warehouse must be open to different tools. Most of the data warehouses employ relational database management systems.

Many of the data warehouses also employ multidimensional database management systems. Data extracted from the data warehouse storage is aggregated in many ways and the summary data is kept in the multidimensional databases (M4DBs). Such multidimensional database systems are usually proprietary products.  

Data Transformation
08.07.13 (1:01 am)   [edit]

Data Transformation

In every system implementation, data conversion is an important function. For example, when you implement an operational system such as a magazine subscription application, you have to initially populate your database with data from the prior system records. You may be converting over from a manual system. Or, you may he moving from a file-oriented system to a modern system supported with relational data-base tables. In either case, you will convert the data front the prior systems. So, what is so different for a data warehouse? I low is data transformation for a data .warehouse inure involved than for an operational system'?

Again, as you know, data for a data warehouse comes from many disparate sources. II' data extraction for a data warehouse poses great challenges data transformation presents even greater challenges. Another factor in the data warehouse is that the data feed is not just an initial load. You will have to continue to pick up the ongoing changes from the source systems. Any transformation tasks you set up for the initial load will be adapted for the ongoing revisions as well.

You perform a number of individual tasks as .part of data transformation. First, you clean the data extracted from each source. Cleaning may just be correction of misspellings or may include resolution of conflicts between state codes and zip codes in the source data, or may deal with providing delimit values for missing data elements, or elimination of duplicates when you bring in the same data from multiple source systems.

Standardization of data elements forms a large part of data transformation. You standardize the data types and field lengths for same data elements retrieved front the various sources. Semantic standardization is another major task. You resolve synonyms and homonyms. When two or 1110re terms from different source systems mean the same thing, you resolve the synonyms. When a single term means many different things in different source systems, you resolve the homonym.

Data transformation involves many forms of combining pieces of data from the differ-em sources. You combine data from single source record or related data elements from many source records. On the other hand, data 'transformation also involves purging source data that is not use rut and separating out source records into new combinations. Sorting and merging of data takes place on a large scale in the data staging area.

In many cases, the keys chosen for the operational systems are field values with built-in meanings. For example, the product key value may be a combination of characters indicating the 'product category, the code of the warehouse where the product is stored, and some code to show the production batch. Primary keys in the data warehouse cannot have built-in meanings. We will discuss this further in Chapter '10. Data transformation also includes the assignment of surrogate keys derived from the source system primary keys.

A grocery chain point-of-sale operational system keeps the unit sales and review amounts by individual transactions at the check-out counter at each store. But in the data warehouse it may not be necessary to keep the data at this detailed level. You may want h summarize the totals by product at each store for a given day and keep the summary total of the sale units and revenue in the data warehouse storage. hi such cases, the data trans formation function would include appropriate summation.

When the data transformation function ends, you have a collection of integrated dat that is cleaned, standardized, and summarized. You now have data ready to load into ear data set in your data warehouse.

70-413 Question 3
06.16.13 (11:21 pm)   [edit]

70-413 Question 3
Your network contains an Active Directory domain named The domain contains an IP Address Management (IPAM) server. You plan to delegate the administration of IPAM as shown in the following table.

You need to recommend which IPAM security group must be used for each department. The solution must minimize the number of permissions assigned to each group. What should you recommend?
To answer, drag the appropriate group to the correct department in the answer area. Each group may be used once, more than once, or not at all. Additionally, you may need to drag the split bar between panes or scroll to view content.