The data pipeline is a concept that allows companies to optimize data transfer, while optimizing and securing it. Today, data is very valuable in many areas and it is important to know the concepts to highlight this data. Find out what a data pipeline is and what current solutions are available to implement this system within your business.
Data pipeline, a simple definition
A data pipeline is a computer concept that refers to the different steps required to transport data from a source to a target. These steps include:
- Data collection;
- Data organization;
- Data transformation;
- The transfer of this data to one or more systems.
The main objective of a data pipeline is to apply all these steps to each piece of data in a consistent way, to enable transformed and secure data transmission.
This type of process can offer many benefits to companies by saving them valuable time by systematizing data transfer.
How does a data pipeline work?
A data pipeline allows data to travel between two or more systems. To do this, a pipeline performs 4 key inseparable actions for the complete data journey within a company.
1.The collection and extraction of raw data
A company must be able to collect all data from various sources and taking various forms, be it Excel tables, file paths (HDFS) or files or subjects (Kafka)... At this stage, the data is neither classified nor structured, let alone processed.
2.The organization of the data
Once the collection is completed, the data must be organized. It is also called data governance. It is in this stage that the data is categorized and organized, to give it a meaning according to the context and needs of the company.
At the same time, the quality and security of the data are monitored to obtain reliable and confidential information.
3. Data transformation
This step is to process the data and convert it into readable information in appropriate reports. Non-essential or truncated data is thus deleted, and the remaining data is processed according to certain essential rules, including:
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- Standardization: define important data and choose how it will be reported and then stored;
- De-duplication: double data are identified and duplicates deleted;
- Verification: the audit is done in an automated manner and is designed to compare the data between them, in order to eliminate unusable data and report system anomalies;
- Ranking: Ranking allows you to group all the data into categories and treat each category in the same way, to save time and obtain treatable and quality data.
4. Data sharing
After transformation, the data is shared in one or more clouds, and then redistributed to appropriate target systems.
The benefits of a data pipeline
You need to start understanding what a data pipeline is and how it works, but in practice, why use a data pipeline in your business? Here are the great advantages of this computer concept.
1. Simple and effective
The operating process remains complex, however, its use as well as its navigation is affordable for any type of user. In addition, the construction of a data pipeline can be done by a computer engineer via the use of Java Virtual Machine (JVM) language, a computer language very common in the field.
2. App comptability
The data pipeline is designed to make it accessible to users and can correlate with current digital marketing strategies. The data pipeline is compatible with a large number of applications and thus prevents the installation of excess software that can overload computer machines.
3. Metadata flexibility
The data pipeline separates manual and automatic records, allowing the user to keep a hold of the metadata. This will make it easy to find the data source, the creator, the tags or the recent changes, if required, in your situation.
4. Built-in components
The components built into the data pipeline will allow you to maintain real control over your data and allow you to enter or exit any data from the pipeline via flow operators. It is also possible, for the more experienced, to customize accessibility options for higher system automation.
How to differentiate Data Pipeline and ETL Pipeline
An ETL pipeline is a subset of the Data Pipeline that extracts, transforms and loads data. However, the main difference between data pipeline and ETL pipeline is that the ETL pipeline uses only one system to extract, process and load data.
The data loading time is longer with an ETL than with a data pipeline, because the latter can be run as a real pipeline while the ETL, using only one system, can only execute commands in hours, which is why ETL systems often work in batches within a data pipeline, thus reducing the time it takes to execute commands.
In addition, an ETL pipeline can only load data to a specific data warehouse,while a data pipeline can load data to selective and specific targets, for example, a data pipeline can load data to Amazon's S3 (Simple Storage Service) compartment, or connect data to a computer system outside Amazon, which is not the case with an ETL pipeline.
Data pipeline solutions available
A data pipeline can complement an already installed system or application. Below are the strategies to implement a data pipeline concept.
1. Cloud
The cloud is widely used within companies to manage and transmit data and its use is almost systematic in data pipeline solutions. However, given the cost of this system, many companies are opting for a multi-Cloud strategy, allowing multiple Cloud systems to be combined while lowering the relative cost and optimizing system security.
2. Open source
Open source is an ideal solution for small businesses wishing to reduce the cost, however, the security of this system remains low and the dependence with suppliers very large. In addition, the use of these tools requires real expertise in the field, to be able to adapt and modify the open source for a better user experience.
3. The use of batch
Batch processing is an alternative for businesses to transport a large amount of data at close intervals. This process allows analysts to combine a large amount of marketing data and provide a reliable and fast decision model.
The data pipeline thus becomes a real added value for companies and allows to optimize the computer system around the new black gold: data.
The concept and solutions currently available to set up a data pipeline in a company are important to increase the quality of information available within your services. Ryax helps you use your data every day to get the full potential!
La Ryax Team.