Boost your company’s growth in just three easy steps
etl-continuous- data

ETL / Continuous Data Processing

ETL denotes Extract, Transform, and Load. Basically, it describes a 3-stage process that includes the extraction and movement of data from various different sources to a specially designed data warehouse for proper and secure storage.

The process helps to prepare data for analyzing and making important decisions. The process is very similar compared to that of Data Migration with a small difference, the format cannot be changed in the process of Data Migration but on ETL we can change the file format.

How does it help?

Become content savant with best content intelligence solutions leading to smarter decision making and success

Data From Different

Bringing Data From Different Sources Easily


Installation Of ETL Procedures


Analysis Of Existing ETL System


Designing ETL Architecture

ETL Testing And Deployment


ETL Support And Maintenance

ETL Data Integration

Want to change things?

To know more about these automated combinations talk with our executives. Ask for a free demo.

How we can help you?

Our content intelligence platform allows marketers to automate all aspects of content creation and promotion procedures using algorithms and artificial intelligence.

We use big data analysis for analyzing the content in real-time which helps marketers get useful data leading to making better decisions and what content to focus on.

Analyze individual pieces of content through natural language processing and identifying characteristics like the tone of voice and style and even make recommendations in terms of SEO strategies.

More Benefits

Support the Sales Team

Reach the Right Customers

Increase Efficiency and Confidence

Prove a Clear ROI

Improve Personalization

How can we help you?

Data Extraction

Proper data extraction from the source system is required for collecting data to process further just before it is analyzed. The data process extraction has to consume less time and resources and that has to be available for the next step in ETL data integration.

Data Cleaning

Here it involves detecting data errors, data redundancies, invalid data, etc. This method, ensures that the consolidated data is best suited for further analysis.

Data Transformation

This step involves transforming the collected source data into a form that matches the target. Here the step consists of converting the units and dimensions of data that can be directly used for the analysis.

Data Loading

In this step, the cleaned and transformed data will be loaded into the target environment. Based on the kind of target database, the data would be loaded either incrementally or in a single go.

Management Of ETL Procedures

Designing a strong ETL architecture and managing it efficiently is necessary for streamlining the whole procedure of data accumulation and processing. Also, the data sources and the whole ETL procedure can be audited frequently to find out and rectify the major errors.

Data Staging

In this step, the data from one process is made available for the next procedure. Such a staging would save the intermediate results of the ETL procedure which can be useful in case the step fails.

Support the Sales Team

Reach the Right Customers

Increase Efficiency and Confidence