Informatica: What are the kinds of lookup? Essay

You can configure the Lookup transmutation to execute different types of search. You can configure the transmutation to be connected or unconnected. cached or uncached: Connected or unconnected. Connected and unconnected transmutations receive input and send end product in different ways. Cached or uncached. Sometimes you can better session public presentation by hoarding the search tabular array. If you cache the search tabular array. you can take to utilize a dynamic or inactive cache. By default. the search cache remains inactive and does non alter during the session. With a dynamic cache. the Informatica Server inserts or updates rows in the cache during the session. When you cache the mark tabular array as the search. you can look up values in the mark and infix them if they do non be. or update them if they do

informatica: Persistent cache and non persistent.

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PERSISTANT CACHEIf you want to salvage and recycle the cache files. you can configure the transmutation to utilize a relentless cache. Use a relentless cache when you know the search tabular array does non alter between session tallies. The first clip the Informatica Server runs a session utilizing a relentless search cache. it saves the cache files to harrow alternatively of canceling them. The following clip the Informatica Server runs the session. it builds the memory cache from the cache files. If the search table alterations on occasion. you can overrule session belongingss to recache the search from the database. NONPERSISTANT CACHEBy default. the Informatica Server uses a non-persistent cache when you enable hoarding in a Lookup transmutation. The Informatica Server deletes the cache files at the terminal of a session. The following clip you run the session. the Informatica Server builds the memory cache from the database

informatica: Dynamic cache?

You might desire to configure the transmutation to utilize a dynamic cache when the mark tabular array is besides the search tabular array. When you use a dynamic cache. the Informatica Server updates the search cache as it passes rows to the mark. The Informatica Server builds the cache when it processes the first search petition. It queries the cache based on the lookup status for each row that passes into the transmutation. When the Informatica Server reads a row from the beginning. it updates the search cache by executing one of the undermentioned actions: Inserts the row into the cache. Updates the row in the cache. Makes no alteration to the cache.

informatica: Difference b/w filter and beginning qualifier?

You can utilize the Source Qualifier to execute the undermentioned undertakings: Join informations arising from the same beginning database. You can fall in two or more tabular arraies with primary-foreign cardinal relationships by associating the beginnings to one Source Qualifier. Filter records when the Informatica Server reads beginning informations. If you include a filter status. the Informatica Server adds a WHERE clause to the default question. Stipulate an outer articulation instead than the default interior articulation. If you include a user-defined articulation. the Informatica Server replaces the articulation information specified by the metadata in the SQL question.

Specify sorted ports. If you specify a figure for sorted ports. the Informatica Server adds an Order BY clause to the default SQL question. Select merely distinct values from the beginning. If you choose Choice Distinct. the Informatica Server adds a SELECT DISTINCT statement to the default SQL question. Make a usage question to publish a particular SELECT statement for the Informatica Server to read beginning informations. For illustration. you might utilize a usage question to execute aggregative computations or put to death a stored process.

informatica: What is Data Transformation Manager Process? How many Threads it creates to treat informations. explicate each yarn in brief. When the work flow reaches a session. the Load Manager starts the DTM procedure. The DTM procedure is the procedure associated with the session undertaking. The Load Manager creates one DTM procedure for each session in the work flow. The DTM procedure performs the undermentioned undertakings: Reads session information from the depository. Expands the waiter and session variables and parametric quantities. Creates the session log file. Validates beginning and mark codification pages. Verifies connexion object permissions. Runs pre-session shell bids. stored processs and SQL. Creates and runs function. reader. author. and transmutation togss to pull out. transform. and load informations.

Runs post-session stored processs. SQL. and blast bids. Sends post-session electronic mail. The DTM allocates process memory for the session and divides it into buffers. This is besides known as buffer memory. The default memory allotment is 12. 000. 000 bytes. The DTM uses multiple togss to treat informations. The chief DTM yarn is called the maestro yarn. The maestro yarn creates and manages other togss. The maestro yarn for a session can make function. pre-session. post-session. reader. transmutation. and writer togss. Maping Thread -One yarn for each session. Fetches session and function information. Compiles the function. Cleans up after session executing. Pre- and Post-Session Threads- One yarn each to execute pre- and post-session operations. Reader Thread -One yarn for each divider for each beginning grapevine. Reads from beginnings. Relational beginnings use relational reader togss. and file beginnings use file reader togss.

Transformation Thread -One or more transmutation togss for each divider. Processes informations harmonizing to the transmutation logic in the function. Writer Thread- One yarn for each divider. if a mark exists in the beginning grapevine. Writes to marks. Relational marks use relational author togss. and file marks use file author togss.

What are indicator files?

informatica: What are indicator files? Autonomic nervous system: . If you use a level file as a mark. you can configure the Informatica Server to make an index file for mark row type information. For each mark row. the index file contains a figure to bespeak whether the row was marked for insert. update. delete. or cull. The Informatica Server names this file target_name. ind and shops it in the same directory as the mark file. to configure it – travel to INFORMATICA SERVER SETUP-CONFUGRATION TAB-CLICK ON INDICATOR FILE SETTINGS.

informatica: Suppose session is configured with commit interval of 10. 000 rows and beginning has 50. 000 rows explain the commit points for Source-based degree Celsiuss Suppose session is configured with commit interval of 10. 000 rows and beginning has 50. 000 rows explain the commit points for Source-based commit & A ; Target-based commit. Assume appropriate value wherever required. a ) For illustration. a session is configured with target-based commit interval of 10. 000. The author buffers fill every 7. 500 rows. When the Informatica Server reaches the commit interval of 10. 000. it continues treating informations until the author buffer is filled. The 2nd buffer fills at 15. 000 rows. and the Informatica Server issues a commit to the mark. If the session completes successfully. the Informatica Server issues commits after 15. 000. 22. 500. 30. 000. and 40. 000 rows.

B ) The Informatica Server might perpetrate less rows to the mark than the figure of rows produced by the active beginning. For illustration. you have a source-based commit session that passes 10. 000 rows through an active beginning. and 3. 000 rows are dropped due to transformation logic. The Informatica Server issues a commit to the mark when the 7. 000 staying rows reach the mark. The figure of rows held in the author buffers does non impact the commit point for a source-based commit session. For illustration. you have a source-based commit session that passes 10. 000 rows through an active beginning. When those 10. 000 rows reach the marks. the Informatica Server issues a commit. If the session completes successfully. the Informatica Server issues commits after 10. 000. 20. 000. 30. 000. and 40. 000 beginning rows.

How to capture public presentation statistics of single transmutation in the function and explicate some of import statistics that can be captured? informatica: How to capture public presentation statistics of single transmutation in the function and explicate some of import statistics that can be captured?

Autonomic nervous system: a ) Before utilizing public presentation inside informations to better session public presentation you must make the followers: Enable monitoring Increase Load Manager shared memory Understand public presentation counters. To see public presentation inside informations in the Workflow Monitor: While the session is running. right-click the session in the Workflow Monitor and take Properties. Snap the Performance check in the Properties duologue box. Click OK. To see the public presentation inside informations file: Locate the public presentation inside informations file.

The Informatica Server names the file session_name. perf. and shops it in the same directory as the session log. If there is no session-specific directory for the session log. the Informatica Server saves the file in the default log files directory. Open the file in any text editor. B ) Source Qualifier and Normalizer Transformations. BufferInput_efficiency -Percentage reflecting how rarely the reader waited for a free buffer when go throughing informations to the DTM. BufferOutput_efficiency – Percentage reflecting how rarely the DTM waited for a full buffer of informations from the reader.

Target BufferInput_efficiency -Percentage reflecting how rarely the DTM waited for a free buffer when go throughing informations to the author. BufferOutput_efficiency -Percentage reflecting how rarely the Informatica Server waited for a full buffer of informations from the author. For Source Qualifiers and marks. a high value is considered 80-100 per centum. Low is considered 0-20 per centum. However. any dramatic difference in a given set of BufferInput_efficiency and BufferOutput_efficiency counters indicates inefficiencies that may profit from tuning. Posted by Emmanuel at 4:31 PM informatica: Autonomic nervous system: Load director is the primary Informatica waiter procedure. It performs the undermentioned undertakings: a. Manages Sessionss and batch programming. b. Locks the Sessionss and reads belongingss. c. Reads parametric quantity files. d. Expands the waiter and session variables and parametric quantities. e. Verifies permissions and privileges.

f. Validates beginnings and marks code pages. g. Creates session log files. h. Creates Data Transformation Manager ( DTM ) procedure. which executes the session.

Assume you have entree to server.

When you run a session. the Informatica Server writes a message in the session log bespeaking the cache file name and the transmutation name. When a session completes. the Informatica Server typically deletes index and informations cache files. However. you may happen index and informations files in the cache directory under the undermentioned fortunes: The session performs incremental collection. You configure the Lookup transmutation to utilize a relentless cache. The session does non finish successfully.

Table 21-2 shows the appellative convention for cache files that the Informatica Server creates: Table 21-2. Cache File Naming Convention Transformation Type Index File Name Data File Name Aggregator PMAGG* . idx PMAGG* . digital audiotape Rank PMAGG* . idx PMAGG* . digital audiotape Joiner PMJNR* . idx PMJNR* . digital audiotape Lookup PMLKP* . idx PMLKP* . digital audiotape If a cache file handles more than 2 GB of informations. the Informatica Server creates multiple index and information files. When making these files. the Informatica Server appends a figure to the terminal of the file name. such as PMAGG* . idx1 and PMAGG* . idx2. The figure of index and information files are limited merely by the sum of disc infinite available in the cache directory.

How to accomplish referential unity through Informatica?
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Using the Normalizer transmutation. you break out repeated informations within a record into separate records. For each new record it creates. the Normalizer transmutation generates a alone identifier. You can utilize this cardinal value to fall in the normalized records. Besides possible in beginning analyzersource analyzer- table1 ( pk tabular array ) -edit-ports-keytype-select primarykey- . table2 ( fktable ) -edit-ports-keytype-select foreign cardinal -select tabular array name & A ; column name from options situated below.

What is Incremental Aggregation and how it should be used?

If the beginning changes merely incrementally and you can capture alterations. you can configure the session to procedure merely those alterations. This allows the Informatica Server to update your mark incrementally. instead than coercing it to treat the full beginning and recalculate the same computations each clip you run the session. Therefore. merely use incremental collection if: Your mapping includes an aggregative map. The beginning changes merely incrementally. ? You can capture incremental alterations. You might make this by filtrating beginning informations by timestamp. Before implementing incremental collection. see the undermentioned issues: Whether it is appropriate for the session What to make before enabling incremental collection

When to reinitialize the aggregative caches Scenario: -Informatica Server and Client are in different machines. You run a session from the waiter director by stipulating the beginning and mark databases. It displays an mistake. You are confident that everything is right. Then why it is exposing the mistake? The connect strings for beginning and mark databases are non configured on the Workstation conatining the waiter though they may be on the client m/c.

Have U created parallel Sessionss How do u make parallel Sessionss? U can better performace by making a concurrent batch to run several Sessionss in analogue on one informatic waiter. if u have several independent Sessionss utilizing separate beginnings and separate function to dwell diff marks u can put them in a coincident batch and run them at the same clip. if u have a complex function with multiple beginnings u can divide the function into several simpler functions with separate beginnings. Similarly if u have session executing a minimum no of transmutations on big sums of informations like traveling level files to presenting country. u can divide the session into multiple Sessionss and run them at the same time in a batch cutting the entire tally clip dramatically

What is Data Transformation Manager?

Ans. After the burden director performs proofs for the session. it creates the DTM procedure. The DTM procedure is the 2nd procedure associated with the session tally. The primary intent of the DTM procedure is to make and pull off togss that carry out the session undertakings. The DTM allocates process memory for the session and split it into buffers. This is besides known as buffer memory. It creates the chief yarn. which is called the maestro yarn. The maestro yarn creates and manages all other togss. If we partition a session. the DTM creates a set of togss for each divider to let concurrent processing. .

When Informatica waiter writes messages to the session log it includes thread type and thread ID. Following are the types of togss that DTM creates: • MASTER THREAD – Main yarn of the DTM procedure. Creates and manages all other togss. • MAPPING THREAD – One Thread to Each Session. Fetches Session and Mapping Information. • Pre And Post Session Thread – One Thread Each To Perform Pre And Post Session Operations. • READER THREAD – One Thread for Each Partition for Each Source Pipeline. • WRITER THREAD – One Thread for Each Partition If Target Exist In The Source grapevine Write To The Target. • TRANSFORMATION THREAD – One or More Transformation Thread For Each Partition.

How is the Sequence Generator transmutation different from other transmutations? informatica: How is the Sequence Generator transmutation different from other transmutations? Autonomic nervous system: The Sequence Generator is alone among all transmutations because we can non add. edit. or cancel its default ports ( NEXTVAL and CURRVAL ) .

Unlike other transmutations we can non overrule the Sequence Generator transmutation belongingss at the session degree. This protecxts the unity of the sequence values generated.

What are the advantages of Sequence generator? Is it necessary. if so why? informatica: What are the advantages of Sequence generator? Is it necessary. if so why? Autonomic nervous system: We can do a Sequence Generator reclaimable. and utilize it in multiple functions. We might recycle a Sequence Generator when we perform multiple tonss to a individual mark. For illustration. if we have a big input file that we separate into three Sessionss running in analogue. we can utilize a Sequence Generator to bring forth primary cardinal values. If we use different Sequence Generators. the Informatica Server might by chance bring forth extra cardinal values. Alternatively. we can utilize the same reclaimable Selenium

What are the utilizations of a Sequence Generator transmutation?
informatica: What are the utilizations of a Sequence Generator transmutation? Autonomic nervous system: We can execute the undermentioned undertakings with a Sequence Generator transmutation: o Create keys o Replace losing values o Cycle through a consecutive scope of figure

What are connected and unconnected Lookup transmutations?
informatica: What are connected and unconnected Lookup transmutations? Autonomic nervous systems: We can configure a affiliated Lookup transmutation to have input straight from the function grapevine. or we can configure an unconnected Lookup transmutation to have input from the consequence of an look in another transmutation. An unconnected Lookup transmutation exists separate from the grapevine in the function. We write an look utilizing the: LKP mention qualifier to name the search within another transmutation. A common usage for unconnected Lookup transmutations is to update easy altering dimension tabular arraies.

What is the difference between connected search and unconnected search?

informatica: What is the difference between connected search and unconnected search? Ans: Differences between Connected and Unconnected Searchs:

Connected Lookup Unconnected Lookup Receives input values straight from the grapevine. Receives input values from the consequence of a: LKP look in another transmutation. We can utilize a dynamic or inactive cache We can utilize a inactive cache Supports user-defined default values Does non back up user-defined default values

What is a Lookup transmutation and what are its utilizations?

informatica: What is a Lookup transmutation and what are its utilizations? Autonomic nervous systems: We use a Lookup transmutation in our function to look up informations in a relational tabular array. position or equivalent word. We can utilize the Lookup transmutation for the undermentioned intents: Get a related value. For illustration. if our beginning tabular array includes employee ID. but we want to include the employee name in our mark tabular array to do our drumhead informations easier to read. ? Perform a computation. Many normalized tabular arraies include values used in a computation. such as gross gross revenues per bill or gross revenues revenue enhancement. but non the deliberate value ( such as net gross revenues ) . ? Update easy altering dimension tabular arraies. We can utilize a Lookup transmutation to find whether records already exist in the mark. ?

What is a search tabular array? ( KPIT Infotech. Pune )
informatica: What is a search tabular array? ( KPIT Infotech. Pune ) Ans: The search tabular array can be a individual tabular array. or we can fall in multiple tabular arraies in the same database utilizing a lookup question override. The Informatica Server queries the search tabular array or an in-memory cache of the tabular array for all entrance rows into the Lookup transmutation. If your function includes heterogenous articulations. we can utilize any of the function beginnings or mapping marks as the search tabular array.

Where make you specify update scheme?

informatica: Where do you specify update scheme? Autonomic nervous system: We can put the Update scheme at two different degrees: • Within a session. When you configure a session. you can teach the Informatica Server to either dainty all records in the same manner ( for illustration. handle all records as inserts ) . or utilize instructions coded into the session function to flag records for different database operations. • Within a function. Within a function. you use the Update Strategy transmutation to flag records for insert. delete. update. or cull.

What is Update Strategy?

informatica: What is Update Strategy? When we design our informations warehouse. we need to make up one’s mind what type of information to hive away in marks. As portion of our mark table design. we need to find whether to keep all the historic informations or merely the most recent alterations. The theoretical account we choose constitutes our update scheme. how to manage alterations to bing records. Update scheme flags a record for update. insert. delete. or reject. We use this transmutation when we want to exercise all right control over updates to a mark. based on some status we apply. For illustration. we might utilize the Update Strategy transmutation to flag all client records for update when the mailing reference has changed. or flag all employee records for cull for people no longer working for the company.

What are the different types of Transformations? ( Mascot )

Informatica: What are the different types of Transformations? ( Mascot ) Ans: a ) Aggregator transmutation: The Aggregator transmutation allows you to execute aggregative computations. such as norms and amounts. The Aggregator transmutation is unlike the Expression transmutation. in that you can utilize the Aggregator transmutation to execute computations on groups. The Expression transmutation permits you to execute computations on a row-by-row footing merely. ( Mascot ) B ) Expression transmutation: You can utilize the Expression transmutations to cipher values in a individual row before you write to the mark. For illustration. you might necessitate to set employee wages. concatenate foremost and last names. or convert strings to Numberss. You can utilize the Expression transmutation to execute any non-aggregate computations.

You can besides utilize the Expression transmutation to prove conditional statements before you end product the consequences to aim tabular arraies or other transmutations. degree Celsius ) Filter transmutation: The Filter transmutation provides the agencies for filtrating rows in a function. You pass all the rows from a beginning transmutation through the Filter transmutation. and so come in a filter status for the transmutation.

All ports in a Filter transmutation are input/output. and merely rows that run into the status base on balls through the Filter transmutation. vitamin D ) Joiner transmutation: While a Source Qualifier transmutation can fall in informations arising from a common beginning database. the Joiner transmutation joins two related heterogenous beginnings shacking in different locations or file systems. vitamin E ) Lookup transmutation: Use a Lookup transmutation in your function to look up informations in a relational tabular array. position. or equivalent word. Import a lookup definition from any relational database to which both the Informatica Client and Server can link. You can utilize multiple Lookup

transmutations in a function. The Informatica Server queries the search tabular array based on the search ports in the transmutation. It compares Lookup transmutation port values to lookup table column values based on the lookup status. Use the consequence of the search to go through to other transmutations and the mark.

What is a transmutation?
informatica: What is a transmutation? A transmutation is a depository object that generates. modifies. or passes informations. You configure logic in a transmutation that the Informatica Server uses to transform informations. The Designer provides a set of transmutations that perform specific maps. For illustration. an Aggregator transmutation performs computations on groups of informations. Each transmutation has regulations for configuring and linking in a function. For more information about working with a specific transmutation. refer to the chapter in this book that discusses that peculiar transmutation. You can make transmutations to utilize one time in a function. or you can make reclaimable transmutations to utilize in multiple functions.

What are the tools provided by Designer?
informatica: What are the tools provided by Designer? Ans: The Designer provides the undermentioned tools: • Source Analyzer. Use to import or make beginning definitions for level file. XML. Cobol. ERP. and relational beginnings. • Warehouse Designer. Use to import or make mark definitions. • Transformation Developer. Use to make reclaimable transmutations. • Mapplet Designer. Use to make mapplets. • Mapping Designer. Use to make functions.

What are the different types of Commit intervals?
Informatica: What are the different types of Commit intervals? Autonomic nervous system: The different commit intervals are: • Target-based commit. The Informatica Server commits informations based on the figure of mark rows and the cardinal restraints on the mark tabular array. The commit point besides depends on the buffer block size and the commit interval. • Source-based commit. The Informatica Server commits informations based on the figure of beginning rows. The commit point is the commit interval you configure in the session belongingss.

What is Event-Based Scheduling?
Informatica: What is Event-Based Scheduling?

Autonomic nervous systems: When you use event-based programming. the Informatica Server starts a session when it locates the specified index file. To utilize event-based programming. you need a shell bid. book. or batch file to make an index file when all beginnings are available. The file must be created or sent to a directory local to the Informatica Server. The file can be of any format recognized by the Informatica Server runing system. The Informatica Server deletes the index file one time the session starts. Use the undermentioned sentence structure to ping the Informatica Server on a UNIX system: pmcmd ping [ { user_name | % user_env_var } { password | % password_env_var } ] [ hostname: ] portno Use the undermentioned sentence structure to get down a session or batch on a UNIX system: pmcmd start { user_name | % user_env_var } { password | % password_env_var } [ hostname: ] portno [ folder_name: ] { session_name | batch_name } [ : pf=param_file ] session_flag wait_flag Use the undermentioned sentence structure to halt a session or batch on a UNIX system: pmcmd halt { user_name | % user_env_var } { password | % password_env_var } [ hostname: ] portno [ folder_name: ] { session_name | batch_name } session_flag Use the undermentioned sentence structure to halt the Informatica Server on a UNIX system: pmcmd stopserver { user_name | % user_env_var } { password | % password_env_var } [ hostname: ] portno

What are the different types of locks?
Informatica: What are the different types of locks? There are five sorts of locks on repository objects: • Read lock. Created when you open a depository object in a booklet for which you do non hold write permission. Besides created when you open an object with an bing write lock. • Write lock. Created when you create or edit a depository object in a booklet for which you have write permission. • Execute lock. Created when you start a session or batch. or when the Informatica Server starts a scheduled session or batch. • Fetch lock. Created when the depository reads information about depository objects from the database. • Save lock. Created when you save information to the depository.

What is Dynamic Data Store?
Informatica: What is Dynamic Data Store? The demand to portion informations is merely every bit pressing as the demand to portion metadata. Often. several informations marketplaces in the same organisation need the same information. For illustration. several informations marketplaces may necessitate to read the same merchandise informations from operational beginnings. execute the same profitableness computations. and arrange this information to do it easy to reexamine. If each informations mart reads. transforms. and writes this merchandise data individually. the throughput for the full organisation is lower than it could be. A more efficient attack would be to read. transform. and compose the information to one cardinal informations shop shared by all informations marketplaces. Transformation is a processing-intensive undertaking. so executing the profitableness computations one time saves clip. Therefore. this sort of dynamic informations shop ( DDS ) improves throughput at the degree of the full organisation. including all informations marketplaces. To better public presentation farther. you might desire to capture

incremental alterations to beginnings. For illustration. instead than reading all the merchandise informations each clip you update the DDS. you can better public presentation by capturing merely the inserts. deletes. and updates that have occurred in the PRODUCTS tabular array since the last clip you updated the DDS. The DDS has one extra advantage beyond public presentation: when you move informations into the DDS. you can arrange it in a standard manner. For illustration. you can snip sensitive employee informations that should non be stored in any informations marketplace. Or you can expose day of the month and clip values in a standard format. You can execute these and other informations cleansing undertakings when you move informations into the DDS alternatively of executing them repeatedly in separate informations marketplaces.

What are Target definitions?
Informatica: What are Target definitions? Detailed descriptions for database objects. level files. Cobol files. or XML files to have transformed informations. During a session. the Informatica Server writes the ensuing informations to session marks. Use the Warehouse Designer tool in the Designer to import or make mark definitions.

. What are Source definitions?
informatica: . What are Source definitions? Detailed descriptions of database objects ( tabular arraies. positions. equivalent word ) . level files. XML files. or Cobol files that provide beginning informations. For illustration. a beginning definition might be the complete construction of the EMPLOYEES tabular array. including the tabular array name. column names and datatypes. and any restraints applied to these columns. such as NOT NULL or PRIMARY KEY. Use the Source Analyzer tool in the Designer to import and make beginning definitions.

What are fact tabular arraies and dimension tabular arraies?
As mentioned. informations in a warehouse comes from the minutess. Fact tabular array in a information warehouse consists of facts and/or steps. The nature of informations in a fact tabular array is normally numerical. On the other manus. dimension tabular array in a information warehouse contains Fieldss used to depict the informations in fact tabular arraies. A dimension tabular array can supply extra and descriptive information ( dimension ) of the field of a fact tabular array. e. g. If I want to cognize the figure of resources used for a undertaking. my fact tabular array will hive away the existent step ( of resources ) while my Dimension tabular array will hive away the undertaking and resource inside informations. Hence. the relation between a fact and dimension tabular array is one to many.

When should you make the dynamic informations shop? Do you necessitate a DDS at all? informatica: When should you make the dynamic informations shop? Do you necessitate a DDS at all? To make up one’s mind whether you should make a dynamic information shop ( DDS ) . see the undermentioned issues: • How much informations do you necessitate to hive away in the DDS? The one chief advantage of informations marketplaces is the selectivity of information included in it. Alternatively of a transcript of everything potentially relevant from the OLTP database and level files. informations marketplaces contain merely the information needed to reply specific inquiries for a specific audience ( for illustration. gross revenues public presentation informations used by the gross revenues division ) . A dynamic information shop is a loanblend of the galactic warehouse and the single informations marketplace.

since it includes all the informations needed for all the informations marketplaces it supplies. If the dynamic informations shop contains about every bit much information as the OLTP beginning. you might non necessitate the intermediate measure of the dynamic informations shop. However. if the dynamic informations shop includes well less than all the informations in the beginning databases and level files. you should see making a DDS presenting country. • • What sort of criterions do you necessitate to implement in your informations marketplaces? Making a DDS is an of import technique in implementing criterions. If informations marketplaces depend on the DDS for information. you can supply that information in the scope and format you want everyone to utilize.

For illustration. if you want all informations marketplaces to include the same information on clients. you can set all the informations needed for this standard client profile in the DDS. Any informations marketplace that reads client informations from the DDS should include all the information in this profile. • • How frequently do you update the contents of the DDS? If you plan to often update informations in information marketplaces. you need to update the contents of the DDS at least every bit frequently as you update the single information marketplaces that the DDS provenders. You may happen it easier to read informations straight from beginning databases and level file systems if it becomes onerous to update the DDS fast plenty to maintain up with the demands of single informations marketplaces. Or. if peculiar informations marketplaces need updates significantly faster than others. you can short-circuit the DDS for these fast update informations marketplaces. •

• Is the information in the DDS merely a transcript of informations from beginning systems. or make you be after to reformat this information before hive awaying it in the DDS? One advantage of the dynamic informations shop is that. if you plan on reformatting information in the same manner for several informations marketplaces. you merely need to arrange it one time for the dynamic informations shop. Part of this inquiry is whether you keep the informations normalized when you copy it to the DDS. • • How frequently do you necessitate to fall in informations from different systems? On juncture. you may necessitate to fall in records queried from different databases or read from different level file systems. The more often you need to execute this type of heterogenous articulation. the more advantageous it would be to execute all such articulations within the DDS. so do the consequences available to all informations marketplaces that use the DDS as a beginning.

What is the difference between PowerCenter and PowerMart?
With PowerCenter. you receive all merchandise functionality. including the ability to register multiple waiters. portion metadata across depositories. and divider informations. A PowerCenter licence lets you create a individual depository that you can configure as a planetary depository. the nucleus constituent of a information warehouse. PowerMart includes all characteristics except distributed metadata. multiple registered waiters. and informations breakdown. Besides. the assorted options available with PowerCenter ( such as PowerCenter Integration Server for BW. PowerConnect for IBM DB2. PowerConnect for IBM MQSeries. PowerConnect for SAP R/3. PowerConnect for Siebel. and PowerConnect for PeopleSoft ) are non available with PowerMart.

What are Shortcuts?
Informatica: What are Shortcuts? We can make cutoffs to objects in shared booklets. Shortcuts provide the easiest manner to recycle objects. We use a cutoff as if it were the existent object. and when we make a alteration to the original object. all cutoffs inherit the alteration. Shortcuts to booklets in the same depository are known as local cutoffs. Shortcuts to the planetary

depository are called planetary cutoffs. We use the Designer to make cutoffs.

What are Sessions and Batches?
informatica: What are Sessions and Batches? Sessions and batches store information about how and when the Informatica Server moves informations through functions. You create a session for each function you want to run. You can group several Sessionss together in a batch. Use the Server Manager to make Sessionss and batches.

What are Reclaimable transmutations?
Informatica: What are Reclaimable transmutations? You can plan a transmutation to be reused in multiple functions within a booklet. a depository. or a sphere. Rather than animate the same transmutation each clip. you can do the transmutation reusable. so add cases of the transmutation to single functions. Use the Transformation Developer tool in the Designer to make reclaimable transmutations

What is a metadata?
Planing a data marketplace involves composing and hive awaying a complex set of instructions. You need to cognize where to acquire informations ( beginnings ) . how to alter it. and where to compose the information ( marks ) . PowerMart and PowerCenter name this set of instructions metadata. Each piece of metadata ( for illustration. the description of a beginning tabular array in an operational database ) can incorporate remarks about it. In drumhead. Metadata can include information such as functions depicting how to transform beginning informations. Sessionss bespeaking when you want the Informatica Server to execute the transmutations. and connect strings for beginnings and marks.