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Interview Questions and Answers

Incremental aggregation allows you to update aggregated data based on changes in the source data. It avoids recalculating the entire aggregation each time, improving performance.

The Workflow Monitor allows you to monitor the status of workflows and sessions. It provides information about the progress of tasks, error messages, and performance metrics.

Performance can be improved through techniques like optimizing SQL queries, using appropriate transformations, partitioning data, increasing buffer pool size, and minimizing data movement.

You can migrate Informatica objects using deployment groups, exporting and importing objects, or using the command-line interface (pmrep).

The Joiner transformation combines data from two or more sources based on a join condition. It supports different join types, such as inner join, left outer join, and full outer join.

A connected lookup is part of the data flow within a mapping, while an unconnected lookup is called as a function from an Expression transformation. Connected lookups are generally more efficient, but unconnected lookups can be reused multiple times within a single mapping.

A parameter is a placeholder for a value that is passed to a mapping or workflow at runtime. A variable is a storage location that can hold a value during the execution of a mapping or workflow. Parameters are read-only during execution, while variables can be modified.

Error handling can be implemented using error ports in transformations, error tables for capturing rejected records, and workflow tasks for handling failed sessions. Workflow variables can also be used to track error conditions.

A mapplet is a reusable object that contains a set of transformations. It can be used in multiple mappings, promoting code reusability and simplifying complex mappings.

Transformations are objects that manipulate data within a mapping. Examples include Filter, Expression, Aggregator, Joiner, Lookup, and Router transformations.

A workflow is a set of instructions that define the order in which tasks are executed. It controls the overall execution of a data integration process, including the execution of mappings and other tasks.

A mapping defines the data transformation logic, while a workflow orchestrates the execution of mappings and other tasks to accomplish a complete data integration process.

You can debug a mapping using the debugger in the Designer tool. This allows you to step through the mapping, examine data values at each transformation, and identify errors.

A session is an instance of a mapping running within a workflow. It represents the actual execution of the data integration process.

There are several session types, including normal load, bulk load, and incremental aggregation.

The Lookup transformation allows you to retrieve data from a lookup table based on a lookup condition. Its used for data enrichment and validation.

Informatica PowerCenter is a data integration platform that provides capabilities for data extraction, transformation, and loading (ETL). It helps organizations integrate data from various sources into a single, unified repository for reporting and analysis.

The key components include the PowerCenter Repository, PowerCenter Server, Repository Manager, Designer, Workflow Manager, and Workflow Monitor.

The PowerCenter Repository stores metadata about sources, targets, transformations, mappings, workflows, and other PowerCenter objects. It acts as the central metadata management system for the platform.

A mapping is a set of transformation rules that define how data is extracted from sources, transformed, and loaded into targets. It is the core building block of data integration processes.

A data warehouse is a system used for reporting and data analysis and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources.

Types of Data Warehouse:

- Enterprise Data Warehouse (EDW).

- Operational Data Store.

- Data Mart.

- Offline Operational Database.

- Offline Data Warehouse.

- Real time Data Warehouse.

- Integrated Data Wa

Data warehouse has four main components: a central database, ETL (extract, transform, load) tools, metadata, and access tools.

Fact tables and dimension tables hold the columns that store the data for the model: Fact tables contain measures, which are columns that have aggregations built into their definitions.

Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis.

- A surrogate key is an artificial or synthetic key that is used as a substitute for a natural key. It is a

In the top-down approach, the data warehouse is designed first and then data mart are built on top of data warehouse.

One dimension is selected for the slice operation.

No. OLTP database tables are normalized and will be adding extra time for queries to return results.

Star schema is the type of multidimensional model which is used for data warehouse.

- In a star schema, only a single join creates the relationship between the fact table and any dimension tables. Design is simple and has high data redundancy.
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ETL process encompasses data extraction, transformation, and loading. ETL systems take large volumes of raw data from multiple sources, convert it for analysis, and loads that data into your warehouse.

Denormalized

Databases store transactional data effectively, making it accessible to end users and other systems. Data warehouses aggregate data from databases and other sources to create a unified repository that can serve as the basis for advanced reporting and ana

This methodology focuses on a bottom-up approach, emphasizing the value of the data warehouse to the users as quickly as possible.

Top Data Warehouse Software:

- Amazon Redshift.

- IBM Db2.

- Snowflake.

- BigQuery.

- Vertica.

Defining Business Requirements.

- Setting up Physical Environments.

- Introducing Data Modeling.

- Choosing Extract, Transfer, Load (ETL) solution.

- Online Analytic Processing (OLAP) Cube.

- Creating the Front End.

Explain with examples that sync with the job description. or Answer appropriately.

Yes we can, but is not advised because Fact tables tend to have several keys (FK), and each join scenario will require the use of different keys.

Dimensional Data Modeling includes of one or more dimension tables and fact tables. Good examples of dimensions are location, product, time, promotion, organization etc.

Metadata in a data warehouse defines the warehouse objects and acts like a directory. This directory helps locate the contents of a data warehouse.

Entity Relationship Model (ER Modeling) is a graphical approach to database design.

Active Data Warehousing is the technical ability to capture transactions when they change, and integrate them into the warehouse.

Real-time Data Warehousing describes a system that reflects the state of the warehouse in real time.

Conformed dimensions make it possible to get facts and measures to be categorized and described in the same way across multiple facts and/or data marts, ensuring consistent reporting across the enterprise.

One fact table.

Cubes are data processing units composed of fact tables and dimensions from the data warehouse.

Time dimensions are usually loaded by a program that loops through all possible dates that appear in the data. Time dimension are used to represent the data over a certain period of time.

Model–view–controller(MVC) is a software design pattern used for developing user interfaces that separate the related program logic into three interconnected elements. Each of these components is built to handle specific development aspects of an applicat

Explain specific instances with respect to the job JD.

NA

(1) Choose the Right Technology when picking up a programming language, Database, Communication Channel.

(2) The ability to run multiple servers and databases as a distributed application over multiple time zones.

(3)Database backup, correcti

Object-oriented programming is a programming paradigm based on the concept of \"objects\", which can contain data, in the form of fields, and code, in the form of procedures. A feature of objects is that objects' own procedures can access and often modify

Explain specific instances with respect to the job JD.

The most common software sizing methodology has been counting the lines of code written in the application source. Another approach is to do Functional Size Measurement, to express the functionality size as a number by performing Function point analysis.

The major parts to project estimation are effort estimation, cost estimation, resource estimate. In estimation, there are many methods used as best practices in project management such as-Analogous estimation, Parametric estimation, Delphi process, 3 Poin

software configuration management (SCM) is the task of tracking and controlling changes in the software code, part of the larger cross-disciplinary field of configuration management. Whereas change management deals with identification, impact analysis, d

Basecamp, Teamwork Projects, ProofHub, Zoho Projects, Nifty, Trello, JIRA, Asana, Podio, etc.

A feasibility study is a study that takes into account all of the related factors of a project — including economic, technological, legal, and scheduling considerations — to assess the probability of completing the project.

Functional requirements are the specifications explicitly requested by the end-user as essential facilities the system should provide. Non-functional requirements are the quality constraints that the system must satisfy according to the project contract,

Validation is the process of checking whether the specification captures the user's needs, while verification is the process of checking that the software meets the specification.

Different Types Of Software Testing - Unit Testing, Integration Testing, System Testing, Sanity Testing, Smoke Testing, Interface Testing, Regression Testing, Beta/Acceptance Testing.

Quality control can be defined as a \"part of quality management concentrating on maintaining quality requirements.\" While quality assurance relates to how a process is carried out or how a product is produced, quality control is more the quality managem