ETL & Reporting

ETL & Reporting

We help enterprise drive busines decisions based on insights
derived from their business data

ETL & Reporting

Extract data from legacy systems

ETL helps extract, cleanse and load data into a target database to improve data quality and establish consistency.

A process of integrating & loading data for computation & analysis

ETL cleanses and organizes data and provides the foundation for data analytics and machine learning workstreams. It helps address specific business intelligence needs and can also tackle more advanced analytics.

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ETL & Reporting
The Benefits & Challenges of ETL

ETL solutions help improve quality by performing data cleansing before loading it to a different repository. ETL is recommended to create smaller target data repositories, which require less frequent updating than other data integration methods.

ETL Tools

Enterprises, in the past, wrote their ETL code. Now, there are options of commercial ETL tools, cloud services, and open sources to write it. Their capabilities include the following:

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Comprehensive Automation and Ease of Use

Leading ETL tools can automate the complete data flow, from data sources to the target data warehouse. Several tools recommend rules for extracting, transforming & loading the data.

A visual, drag-and-drop interface

One can use the functionality of a visual, drag-and-drop interface for specifying rules and data flows.

Support for Complex Data Management

Complex data management support includes help with data integrations, complex calculations, and string manipulations.

Security and Compliance

The ideal ETL tools encrypt data in motion and at rest. In addition, they are certified and compliant with government or industry regulations, such as GDPR and HIPAA.

Change Data Capture (CDC)
Change Data Capture (CDC)

CDC identifies and captures the source data that has changed. It helps move that data to the target system. For example, one can use it to reduce the resources required during the ETL “extract” step.

Data Replication
Data Replication

Data replication is a process of copying changes in data sources in real-time, and in batches, to a central database. It is often listed as a data integration method and is used to create backups.

Data Virtualization
Data Virtualization

It is a software abstraction layer to create an integrated, unified, and entirely usable data view —without physically transforming, copying, or loading the source data to a target system. This functionality allows an organization to create virtual data warehouses.

Stream Data Integration (SDI)
Stream Data Integration (SDI)

SDI continuously consumes data streams in real-time and transforms & loads them to a target system for analysis. The essential word here is 'continuously.' Instead of integrating data snapshots extracted from sources at a given time, SDI integrates data constantly.

ETL & Reporting
Integration of real-time, streaming data for artificial intelligence (AI) applications.

One can use APIs (Application Programming Interfaces) using EAI (Enterprise Application Integration) in place of ETL for a more flexible, scalable solution that includes workflow integration.

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