Data Engineering and Analytic for Better Business Intelligence

Data Engineering and Analytics

Changing the Way the World Lives and Works

Data management and governance are core essential to ensure efficient data analysis and intelligence. The art of achieving this excellence is what Entrans terms “Data Engineering”.

Data engineering to intelligence is a process but the way to achieve it is distinct in every use case that we have solved so far. The following image describes the fundamental steps that we take to ensure we achieve the best business outcome for your requirement

Data Preparation and Loading (ETL or ELT process)

Data Preparation is one of the most critical steps in building a data layer. The aim of this process is to reduce the errors or skewed information from the data and create information that’s useful and relevant to achieve the business outcome.
Every use case requires different tools to be used in achieving this, Entrans however, brings in frameworks and experience working in AI to make this process more effective and faster

Intelligent Join Detection

Use the power of AI to detect exact or fuzzy match single or multi-column join criteria and combine datasets for data feature enrichment

Scenario

The name of an individual might be available in different datasets in different ways. Just imagine correlating this data across datasets? We help make it simple using AI.

Intelligent Data Ingest

Automatically detect file types at ingestion time and intelligently flatten complex structures into tabular representations for learning dataset creation.

Scenario

Your dataset may be in different formats, however, during its ingestion we expect all the data to flatten out into columnar formats. This is possible using AI.

Intelligent Production Data Pipelines

Automate/schedule data preparation and loading to run at regular intervals with automatic detection and inclusion of preceding data preparation and loading steps to create an entire data flow that’s automated and repeatable.