Submit a request for ETL process automation

This service is designed to manage ETL processes and provide data quality control.

Automation of ETL processes

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What is ETL Automation for?

Data Integration
Cost reduction
Data quality assurance
The service allows organisations to collect data from various sources such as databases, applications, external systems and many others.
Automating ETL processes reduces operational costs because it reduces the need for manual operations and human intervention.
Automated processes within this service may include checking and correcting data and ensuring it meets standards and requirements.
Accelerating access to data
Automating ETL processes reduces time delays between data collection and its availability for analytics and decision-making.
The service provides tools to monitor ETL processes and report on task performance.
Monitoring and reporting

Benefits of automating ETL processes

Efficiency and speed
Data quality and accuracy
Reduced costs and increased efficiency
  • Automated ETL processes can include automatic validation, normalisation and standardisation of data to help improve data quality.
  • This reduces human error and provides more accurate and reliable data for analysis and decision-making.
  • Automating ETL processes allows routine tasks to be completed much faster, as computers are able to work continuously and on large amounts of data without fatigue.
  • This is especially important for businesses, where reducing the time between data collection and access can be critical to operational decisions and competitiveness.
  • Automating ETL processes reduces the need for a lot of manual labour, which reduces operational costs.
  • It also allows employees to use their time more efficiently on more strategic tasks such as data analysis and strategy development, helping to improve productivity and business competitiveness.

We use the following state-of-the-art technologies to automate ETL processes

Python
Apache NiFi
Apache Airflow
Apache NiFi is designed to automate and manage data flows, including data collection, transformation, and loading (ETL).
NiFi has a graphical user interface that allows you to create and customise data flows using off-the-shelf components.
One of NiFi's key advantages is its ability to process data in real time, which is useful for scenarios where rapid response to data changes is required.
Apache Airflow is designed for managing and scheduling workflows, including ETL processes.
Airflow provides a graphical interface for creating and visualising workflows as directed acyclic graphs (DAGs), where each task is defined as a separate block in the graph.
Airflow provides capabilities for scheduling task execution, monitoring execution, re-execution, and creating alerts and reports.
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Technical specification for assessment
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