Data ingestion is an important aspect in the universe of big data and analytics, as it enables decision makers to make better decisions.
In fact, this expression refers to the process of transferring data from one or more sources to a destination site that enables its analysis and processing.
As we know, data can have various formats and especially come from multiple sources such as:
- data lake;
- internet of Things devices;
- database;
- APP;
- data warehouse.
There are three ways to carry out a “Data Ingestion” process:
- realize it in real time;
- Taking advantage of the batch;
- using a ‘Lambda architecture (combination of the previous models).
These types of activities, as we can imagine, have numerous advantages for companies, attributable to the possibility of adopting data-driven approaches.
In marketing, this all translates into the possibility of optimizing the effectiveness of campaigns and activities starting precisely from data analysis and in-depth knowledge of one’s target audience.
The concept of Data Ingestion is also related to that of ETL (extract, transform, load).
Unlike this, the latter is a data integration process that helps organizations extract data from various sources to a single DB, transforming it before distribution.
