Data pipeline: how to create solid data pipelines

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Data plays a crucial role in business growth. However, companies sometimes struggle to fully leverage its potential. Building a solid data pipeline is one of the keys to solving this challenge.

Data pipelines are sets of tools and processes used to automate the movement and transformation of data between a source system and a target repository.

When the data pipeline is solid, companies can efficiently manage, analyze and organize all their information. But how can you achieve a robust and efficient pipeline? We'll tell you about it in this article.

What is a data pipeline architecture and what benefits does it bring?
Organizations are constantly using data from different sources. It is in this multiplicity of origins that the richness of data lies, but also where complexities arise.

Since source systems often have different data processing and indonesia phone number lead storage methods than destination systems, it is necessary to implement an efficient and systematized mechanism that allows identifying, collecting and analyzing information to transform data into knowledge .

After all, 80% of business leaders believe that data is essential to corporate decision-making , while 73% believe that it helps reduce uncertainty and make more accurate decisions.

Despite these percentages, according to a study carried out by IDC on 1,200 companies globally, only 20% of them recognize themselves as capable of converting data into actionable insights.

So how can organizations turn this situation around and get the most value out of the data they collect? The answer is: by creating a data pipeline .

It is a series of processing steps that aim to prepare business data so that it can be properly analyzed.

Data pipeline software automates the process of extracting data from disparate source systems, transforming, combining, and validating that data, and then loading it into the target repository.

By designing a data pipeline, it is possible to eliminate data silos and create a holistic and unified image of the business. In this way, organizations can apply Business Intelligence (BI) and data analytics tools to create data visualization projects and dashboards that allow obtaining and sharing practical information.

In addition to enabling business intelligence, the implementation of data pipelines:

Improves data quality . Pipelines standardize formats, eliminate redundancy, and check for errors, ensuring data quality .
It facilitates data integration . Designing a pipeline allows you to integrate data sets from disparate sources, comparing their values and correcting inconsistencies.
Enables real-time access to data . Data pipelines ensure that the right people or systems can access the right data at the right times. As a result, they enable organizations to respond quickly to changing market conditions and take advantage of emerging opportunities.
Provides scalability . As businesses experience data growth, data pipelines can scale to handle larger workloads without compromising performance. This is a key capability in today’s environment of constant and exponential growth in the number of records.
Drives efficiency in data processing . Data pipelines provide the ability to automate data transformation tasks so that data engineers can focus on the most valuable information. They also help to more quickly process unprocessed data that loses value over time.
Facilitates data governance . Creating a data pipeline architecture makes it easier to track and monitor data access and usage. In this way, it contributes to compliance with data governance policies , ensuring that records are managed, processed and stored in accordance with current regulations.
How to create a solid data pipeline
Designing a robust data pipeline requires carrying out a process that is divided into several steps.

Each of these stages must be carefully planned and executed, since the decisions made in them directly impact the functioning of the pipeline and the results it provides.