Back

What is a Data pipeline and how does it work?

AINSYS offers tools for setting up efficient data pipelines, reducing setup time and improving data management for businesses of all sizes.

What is a Data pipeline and how does it work?

A data pipeline is a set of tools and methods for transporting data from  sources to the destination. AINSYS provides businesses of any size with the best tools for setting up data pipelines via data warehouses and pre-configured pipelines that facilitate data normalization for non-technical personnel. Our approach to data pipeline management reduces time to MVP for customers’ teams from weeks and months to minutes and hours.

Imagine that you just bought a popular bakery. Since it has its own website customers place orders 24/7. That means you have to process a lot of data, such as customers’ info, what cakes they order, credit card information, and many other details. Thanks to online transaction processing (OLTP) programs, including various databases and apps, your bakery is prospering.

As the bakery’s owner, not only do you have to properly accept orders but you also have to closely watch your overall results, such as analyzing which cakes are popular and which ones should be taken off the shelf. For that, you collect transactional data and move it from the database that includes order info to another system that handles the rest of your data, transforming it in the process.

Moving data this, moving data that… You need infrastructure and software to do that. You need a data pipeline.

What is a data pipeline?

A data pipeline is a set of tools and methods for transporting data from the source (often many separate sources) to the destination. It’s important to note that data is changed and optimized during the journey, eventually arriving at a state that allows analysis and producing new business insights.

So, all that concerns accumulating, organizing, and transporting data is a data pipeline. Many of the manual tasks needed to process, shorten, and improve lengthy data loads are automated by modern software. It also takes care of loading raw data into spreadsheets for interim storage and then modifying it before adding it to the final database.

Dealing with data pipelines requires data integration — for example, processing and storing transaction data and completing a sales trend analysis for the entire quarter. To do the analysis, you will need to pull data from multiple sources into a single storage location and prepare it for analysis. As a result, a data pipeline enables the resolution of “origin-destination” issues, particularly with enormous amounts of data.

Key components

Different researchers identify basic data pipeline components differently. But, according to David Wells, the senior research analyst at Eckerson Group, at a high level, a data pipeline consists of eight types of components:

  • Origin

The point at which data first enters the pipeline, for example, the company’s IoT devices, social media, APIs, or public datasets;

  • Destination

The final point of delivery. Depending on the use case, data can be sourced for data visualization and analytical tools or relocated to storage such as a data lake or a data warehouse.

  • Dataflow

Processes that allow data to move, including any transformations;

  • Storage

Databases for persisting data during various stages as it moves through the pipeline. Data storage options are determined by a variety of parameters, including frequency and volume of queries to a storage system, uses of data, and so on;

  • Processing

Steps for ingesting and transforming data. It focuses on how to support data movement. For example, data can be ingested by extracting it from source systems, replicating it from one database to another (database replication), streaming it, etc.;

  • Workflow

Sequencing and dependency management of processes;

  • Monitoring

Ensuring a healthy and efficient pipeline by checking how the data pipeline and its stages are working.

  • Technology

Software for enabling dataflows, storing, processing, workflows, and monitoring. It plays the most crucial role since the right equipment can help your business rise to the top or tank it within days.

Managing data pipelines

It is impossible to overstate the importance of paying enough attention to each component, as well as connecting them. Your imaginary bakery needs every step of the way to be properly organized. Providing the right tools plays a key role in this.

AINSYS provides businesses of any size with the best tools for setting up data pipelines via data warehouses and pre-configured pipelines that facilitate data normalization for non-technical personnel. Our approach to data pipeline management reduces time to MVP for customers’ teams from weeks and months to minutes and hours. You will also be able to integrate new IT solutions into your organization’s workflow with lighting-fast accuracy even after the end of the setup process.

However, every business owner still needs to be acutely aware of how their company is structured. This starts with determining what type of pipeline you need created.

1. Batch pipelines

Batch data pipelines do exactly what you think — process data in batches, gathering it over a period of time and executing the procedure at regular intervals.

When you think of a standard data analysis methodology, you are probably picturing batch pipelines. Indeed, batch processing has been crucial for decades in analytics and business intelligence, and it continues to be so today. No surprise there — its familiarity and simplicity have helped many businesses to streamline processes.

You and we both know that for the company to run smoothly and efficiently, results should be delivered much faster than possible with batch pipelines. That’s why streaming pipelines were introduced.

2. Streaming pipelines

Streaming pipelines employ real-time data processing, commonly referred to as event streaming. It is a method of continually processing data as it is collected in a matter of seconds or milliseconds. In an event-based architecture, real-time systems respond faster to new data inputs. While real-time data pipelines can be utilized for analytics, they are required for systems that require data to be operationalized instantly.

For example, your imaginary bakery’s website is better off instantaneously managing inventory to avoid conflicts (for example, selling the same cake to two different customers), monitoring stock, and providing communication with clients.

Of course, the advantages of real-time streaming and data analysis include the ability to rapidly investigate our data and automate processes. We take modern automating programs for granted but our companies would not be able to function without them.
However, modern software for creating data pipelines often lacks connectivity and processing capabilities for data, making integrating vital business systems difficult.

AINSYS solves issues that both batch and streaming pipelines might cause when you set up business processes. Your teams can use our no-code tools to transform and test data pipelines on the fly, eliminating the need to collect requirements and create long design and technical documentation.


STANFORD EUROPE LIMITED
16 Great Queen Street
Covent Garden London WC2B 5AH
Get More From Your Demo
Thanks for signing up! To make the most of your demo, please fill out this short form to help us tailor the discussion to your needs.
Tailor Your Demo
Fill out a short form a more personflized expierence.
Let’s get
acquainted!
Connect with Our CEO on LinkedIn & Schedule a virtual coffee:
Instant Access
‍
Can't wait? Jump into a live chat with our team now and explore a live demo of AINSYS in action.
Tailor Your Demo
Start a live chat now and gain instant access to a live demo.