Friday, April 9, 2021

Informatica Interview Questions And Answers For 5 Years Experience

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  • [DOWNLOAD] Informatica Interview Questions And Answers For 5 Years Experience

    The user can go to the Properties tab and in SQL query tab write the distinct query. A user can use Aggregator and select ports as key to getting distinct values. If a user wishes to find duplicates in the entire column, then all ports should be...

  • [FREE] Informatica Interview Questions And Answers For 5 Years Experience | HOT

    This cache is updated as and when data is read. If a source has duplicate records, the user can look in Dynamic lookup cache and then the router selects only one distinct record. What is the difference between Source qualifier and filter...

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    What are some examples of Informatica ETL programs? Some basic Informatica programs are: Mappings: A mapping is designed in the Designer. It defines all the ETL processes. Data are read from their original sources by mappings before the application of transformation logic to the read data. The transformed data is later written to the targets. Workflows: The processes of runtime ETL are described by a collection of different tasks are known as workflow. Workflows are designed in the Workflow Manager. Task: This is a set of actions, commands, or functions that are executable. How an ETL process behaves during runtime can be defined by a sequence of different tasks. Which development components of Informatica have the highest usage? There are many development components in Informatica. However, these are the most widely used of them: Expression: This can be used to transform data that have functions. Lookups: They are extensively used to join data.

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    Sorter and Aggregator: This is the right tool for sorting data and aggregating them. Source qualifiers: Many people use this component to convert source data types to the equivalent Informatica data types. Transaction control: If you want to create transactions and have absolute control over rollbacks and commits, count on this component to bail you out. What are the uses of ETL tools? ETL tools are quite different from other tools. They are used for performing some actions such as: Loading important data into a data warehouse from any source known as Target.

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    Extracting data from a data warehouse from any sources such as database tables or files. Transforming the data received from different sources in an organized way. Some of the notable sources where data are received include SAP solutions, Teradata, or web services.

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    Branding, etc. It is a data-driven methodology and approach. It removes defects in any process from manufacturing to finance. QMS means quality management system. It documents all the needed information and operational controls. It consists of reporting, monitoring, and training to make sure that company delivers the continuous product. CAPA is a good manufacturing practice concept, it which product failures are investigated to correct their current occurrence and also prevent similar occurrences in the future.

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    Document control is a function of managing and controlling product documentation. Yes, sometimes I had faced issues regarding old pages being rendered from cache to the user. In such situation, I clear the cache and then try to investigate the cause. Many times these issues happen because of the comparatively high refresh interval. At that time, it is important to reduce the cache refresh interval. Here you should come up with something which would not strain your credibility.

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    Describe small mistake made by you in the past and positive lesson learned from that mistake. Multitasking Outstanding verbal and personal communication Ability to perform under pressure 11 Do you think teamwork is a critical part of the production support job? No, production support person mostly works alone. However, in some cases, product support specialist can be part of a support team. It always helps to be a good team player. It is a combination of both technical expertise and soft skills. I try to look for the error in the in the last n minutes when the issue occurred.

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    However, If the issue is still happening, then I tail the logs for the different application server to see the error snippets found in the live logs. Level 2 Support — It is technical support for the application or software. They check the flow of the application and can go deep into the issue and fix it if they can if not escalate further. This kind of production support executive should have vast experience on a particular technology platform. Level 3 Support: This kind of product support professionals work on enhancements, and bug fixes. They most like to have expertise on one or two technology platforms like Oracle database or a Windows Admin.

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    Consistency: It is an essential skill for the production support job. It can be achieved by offering an accurate solution to the customer. Attention to Detail: Production support executive should have great precision, particularly when operating dangerous machinery. As a production support executive, you should have the ability to lead a team and resolve problems that may arise between your team members. I read books, blogs, and articles related to production support. I have exemplary time management skills.

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    I also know how to manage and present data using CRM. System security means stopping viruses and malware programs from reaching the computer system. It can be achieved by using methods like antivirus, firewall installation and by restricting activities of the online users. Yes, I have created few aliases and saved them within my profile file so that the system loads each time automatically when I log onto the server.

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    Navigator is used to perform the following activities: It is used to connect with Repository service. It is used to open folders. It is used to copy objects and to create the shortcuts. Workspace Workspace is a space where we do the coding. In a workspace, we can create as well as edit the repository objects such as sources, targets, mapplets, mappings, and transformations. Toolbar Different components in the toolbar are available such as Repository, edit, tools, versioning, windows, and help. Status bar The status bar displays the status of the current operation. The domain is a collection of nodes machines and services, i. It is an administrative unit from where you manage or control things such as configurations, users, security. The domain is an environment where you can have a single domain as well as multiple domains.

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    For example, we have three departments such as development, test, and production; then we will have a domain for each department, i. Workflow Manager is used to create Workflow and Worklet. Workflow Workflow is a set of instructions used to execute the mappings. The workflow contains various tasks such as session task, command task, event wait task, email task, etc. It is also used to schedule the mappings. All the tasks are connected to each other through links inside a workflow. After creating the workflow, we can execute the workflow in the workflow manager and monitor its progress through the workflow monitor. Worklet Worklet is an object that groups a set of tasks which can be reused in multiple workflows.

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    A worklet is similar to a workflow, but it does not have any scheduling information. In worklet, you can group the tasks in a single place so that it can be easily identified. Workflow Monitor is used to monitor the execution of workflows or the tasks available in the workflow. It is mainly used to monitor the progress of activities such as Event log information, a list of executed workflows, and their execution time. Workflow Monitor can be used to perform the following activities: You can see the details of execution You can see the history of workflow execution You can stop, abort, or restart the workflows. It displays the workflows that have been executed at least once. It consists of the following windows: Navigator window: It displays the repositories, servers, and repositories objects that have been monitored.

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    Output window: It displays messages coming from the Integration service and Repository service. Time window: It displays the progress of workflow execution. Gantt Chart view: It displays the progress of the workflow execution in a tabulated form. Task view: It displays the details about the workflow execution in a report format. Transformations are used to transform the source data into target data. It ensures that the data will be loaded to the target database based on the requirements of the target system. A transformation is basically a repository object that can read, modify, and passes the data from source to the target. There are two types of transformations: Active transformation Active transformation is a transformation which can modify the number of rows that passes from source to the target, i.

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    Passive transformation Passive transformation is a transformation that does not eliminate the number of rows, i. SQ stands for Source Qualifier transformation that selects the records from multiple sources, and the sources can be relational tables, flat files, and Informatica PowerExchange services. It is an active and connected transformation. When you add the source tables in mapping, then Source Qualifier is added automatically. It displays the transformation types, i. In the case of SQ transformation datatypes, source datatype does not match with the Informatica compatible datatype then the mapping will become invalid when you save it.

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    SQ transformation is an active transformation as you can apply all the business rules and filters to overcome the performance issue. By using SQ transformation, you can apply filters on the data by applying joins on the tables. Source Qualifier transformation can also join homogeneous tables, i. Expression Transformation is a passive and connected transformation. It is used to manipulate the values in a single row. Examples of expression transformation are concatenating the first name and last name, adjusting the student records, converting strings to date, etc.

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    It also checks the conditional statements before passing the data to other transformations. Expression transformation uses numeric and logical operators Following are the operations performed by the expression transformer are: Data manipulation It performs operations such as concatenation, truncation, and round. Datatype conversion It can also convert one data type into another data type. Data cleansing It checks for nulls, test for spaces, test for numbers.

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    Manipulate dates It can also manipulate the dates. Scientific calculations and numerical operations It also performs the exponential, log, modulus, and power operations. There are three types of ports used in Expression Transformation: Input An input port consists of values which are used in the calculation.

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    For example, we need to calculate the total salary; then it will be calculated only when we know the salary and incentives of an employee. Output We provide expression to each output port, and the return value of the output port should match the return value of the expression. Variable It is a temporary variable used in the calculation.

  • Informatica Interview Questions You Should Know | TestingBrain

    It is also used in case-sensitive sorting, and also used to specify whether the output rows should be distinct or not. Sorter transformation is an active transformation as it eliminates duplicates. Properties of Sorter Transformation: Sorter cache size An integration service uses sorter cache size property to determine the maximum amount of memory required to perform the sort operation.

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    Case Sensitive You can also enable the case-sensitive property; in such case, an integration service will give more priority to the uppercase characters than lowercase characters. Work directory Work directory is a directory where integration service creates temporary files while sorting the data. When data is sorted, then all the temporary files will be removed from the work directory. Distinct Output Rows This property is used by the integration service to produce the distinct output rows. Tracing Level The tracing level is a property that controls the number, type of sorter error, and status messages that integration service writes to the session log. Null Treated Low Enable this property when you want integration service treat null value lower than other value. Disable this property when you want to treat the null value higher than the other value. Aggregator transformation is a connected and active transformation.

  • Top 85 Informatica Interview Questions & Answers | For Freshers

    It is used to perform aggregate functions over a group of rows such as sum, average, count, etc. For example, if you want to calculate the sum of the salary of all the employees, then an aggregator transformation is used. Aggregator transformation uses the temporary main table to store all the records, and perform the calculations. Components of Aggregator transformation: Aggregate cache An integration service uses the aggregate cache to store the data until the aggregate calculation is completed. It stores the group values in index cache and row data in the data cache. Aggregate expression An aggregate expression is provided to the output port and output port can also contain non-aggregate expressions and conditional clauses. Group by port This property is used to create the groups. Groups can be input, output, or any variable port. Sorted input Sorted input property is used to improve the session performance.

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    In order to use sorted input, you need to pass the data to aggregator transformation sorted by group by port either in ascending or in descending order. Filter transformation is an active and connected transformation. It filters out the rows which are passed through it, i. It applies the filter condition on the group of data. This filter condition returns an either true or false value. If the value is true means that the condition is satisfied, then data is passed through, and if the value is false means that the filter condition is not satisfied, then integration service drops the data and writes the message to the session log. Joiner Transformation is an active and connected transformation. It allows you to create the joins in Informatica, similar to the joins that we create in database. In joiner transformation, joins are used for two sources and these sources are: Master source Detail source In joiner transformation, you need to choose which data source will be Master, and which data source will be Detail.

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    There are four types of joins used in a joiner transformation: Master outer join In Master outer join, the resultset contains all the records from the Detail source and the matching rows in the master source. This join will be similar to the Right join in SQL. Detail outer join In Detail outer join, the resultset contains all the records from the Master source and the matching rows in the Detail source. This join will be similar to the Left join in SQL. Full outer join In Full outer join, the resultset contains all the records from both the sources, i. Normal join In Normal join, the resultset contains only the matching rows between Master and Detail source. This join is similar to the inner join in SQL. Router transformation is an active and connected transformation. Router transformation is similar to the filter transformation as both the transformations test the input data based on the filters.

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    In Filter transformation, you can apply only one filter or condition, and if the condition is not satisfied, then a particular is dropped. But in Router transformation, more than one condition can be applied. Therefore, we can say that the single input data can be checked on multiple conditions. Rank transformation is an active and connected transformation. It filters the data based on groups and ranks. For example, if you want to get top 3 salaried employees department wise, then this will be achieved by the rank transformation.

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    Question Answer : Data cubes are commonly used for easy interpretation of data. It is used to represent data along with dimensions as some measures of business needs. Each dimension of the cube represents some attribute of the database. Answer : Data cleaning is also known as data scrubbing. Data cleaning is a process which ensures the set of data is correct and accurate. Data accuracy and consistency, data integration is checked during data cleaning. Data cleaning can be applied for a set of records or multiple sets of data which need to be merged. Answer : An extension of data mining can be used for slicing the data the source cube in discovered data mining. The case table is dimensioned at the time of mining a cube. Answer : A stage of data mining is a logical process for searching large amount information for finding important data. Stage 1: Exploration: One will want to explore and prepare data. The goal of the exploration stage is to find important variables and determine their nature.

  • Top 85 Informatica Interview Questions & Answers | For Freshers

    Stage 2: pattern identification: Searching for patterns and choosing the one which allows making best prediction, is the primary action in this stage. Stage 3: Deployment stage: Until consistent pattern is found in stage 2, which is highly predictive, this stage cannot be reached. The pattern found in stage 2, can be applied for the purpose to see whether the desired outcome is achieved or not. The US FBI uses data mining for screening security and intelligence for identifying illegal and incriminating e-information distributed over internet. What Is Data Purging? Answer : Deleting data from data warehouse is known as data purging. Usually junk data like rows with null values or spaces are cleaned up. Data purging is the process of cleaning this kind of junk values. What Is Bus Schema? Answer : A BUS schema is to identify the common dimensions across business processes, like identifying conforming dimensions.

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