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Informatica ETL

Informatica ETL is used to data extraction, and it is based on the data warehouse concept, where the data is extracted from multiples different databases.

Informatica ETL


The Ab Intio multinational Software Company invented the ETL tool. This company is located outside of Lexington, Massachusetts. The United States framed GUI Based parallel processing software that is called ETL.

Implementation of ETL Tool

Informatica ETL

1. Extract

The data is extracted from different sources of data. The relational databases, flat files, and XML, Information Management System (IMS), or other data structures are including in the standard data-source formats.

Instant data validation is used to confirm whether the pulled data from the sources have the correct values in a given domain.

2. Transform

To prepare and to load into a target data source, we applied a set of rules and logical functions on the extracted data. The cleaning of data means passing the correct data into the target source.

According to the business requirements, we can apply many transformation types in the data. Some transformation types are Key-based, column or row-based, coded and calculated values, joining different data sources, and many more.

3. Load

In this phase, we load the data into the target data source.

All three phases do not wait for each other for starting or ending. All three-phase are parallelly executed.

Uses in Real-Time Business

Informatica company provides data integration products for ETL such as data quality, data masking, data virtualization, master data management, data replica, etc. Informatica ETL is the most common Data integration tool which is used for connecting & fetching data from different data sources.

To approach this software, some use cases are given below, such as:

  1. An organization is migrating a new database system from an existing software system.
  2. To set up a Data Warehouse in an organization, the data need to move from the Production to Warehouse.
  3. It works as a data cleansing tool where data is corrected, detected, or removed inaccurate records from a database.

Features of ETL Tool

Here are some essential features of the ETL tool, such as:

1. Parallel Processing

ETL is implemented by using a concept of Parallel Processing. Parallel Processing is executed on multiple processes that running simultaneously. ETL is working on three types of parallelism, such as:

  • By splitting a single file into smaller data files.
  • The pipeline allows running several components simultaneously on the same data.
  • A component is the executables processes involved for running simultaneously on different data to do the same job.

2. Data Reuse, Data Re-Run, and Data Recovery

Each data row is provided with a row_id, and a piece of the process is supplied with a run_id so that one can track the data by these ids. To complete certain phases of the process as we create checkpoints. These checkpoints tell the need to re-run the query for task completion.

3. Visual ETL

The PowerCenter and Metadata Messenger are advanced ETL tools. These tools help to make faster, automated, and impactful structured data according to the business requirements.

We can create a database and metadata modules with a drag and drop mechanism as a solution. It can automatically configure, connect, extract, transfer, and loads the data into the target system.

Characteristics of ETL Tool

Some attributes of the ETL tool are as follows:

  1. It should increase data connectivity and scalability.
  2. It should be capable of connecting multiple relational databases.
  3. It should support CSV extension data files then the end-users can import these files easily or without any coding.
  4. It should have a user-friendly GUI so that the end-users easily integrate the data with the visual mapper.
  5. It should allow the end-user to customize the data modules according to the business requirements.

Why do you need ETL?

It is common for data from disparate sources to be brought together in one place during creating a data warehouse so that it can be analyzed for patterns and insights. It's okay if data from all these sources had a compatible schema from the outset, but it happens very rarely.

ETL takes the heterogeneous data and makes it homogeneous. The analysis of different data and derive business intelligence is impossible without ETL.

ETL Tool Products and Services

Informatica -ETL products and services are used to improve business operations, reduce big data management, provide high security of data, data recovery under unforeseen conditions and automate the process of developing and artistically design visual data. The ETL tool product and services are divided into the following:

  1. ETL with Big Data
  2. ETL with Cloud
  3. ETL with SAS
  4. ETL with HADOOP
  5. ETL with Metadata
  6. ETL as Self-service access
  7. Mobile optimized solution and many more.

Why is ETL Tool so trending?

The following qualities of ETL tool being it so trending, such as:

  1. ETL tool has accurate and automates deployments.
  2. It minimizes the risks of adopting new technologies.
  3. It provides highly secured data.
  4. It is self- Owned.
  5. It includes recovery from a data disaster.
  6. It provides data monitoring and data maintenance.
  7. It has an attractive and artistic visual data delivery.
  8. It supports the centralized and cloud-based server.
  9. It provides concrete firmware protection of data.

Side effects of ETL Tool

The organization continuously depends on the data integration tool. It is a machine, and it will work only after receiving a programmed input.

There is a risk of complete crashing of the systems, and it tells how good the data recovery systems are built. Any misuse of simple data may create a massive loss in the organization.

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