What Is Stream Processing? (Plus Uses and Related Jobs)

By Indeed Editorial Team

Published August 4, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Professionals can use an array of technologies and methods, including stream processing, to help them manage vast amounts of organizational data. Stream processing can help companies continually process data in real-time, increase operational efficiency and optimize their end-users' experience. Knowing more about the various components of and uses for stream processing methodology might benefit your professional goals or workplace. In this article, we discuss what stream processing is, explain how it works, review its benefits, provide examples of when you might use this data management technique and explore various careers that may involve stream processing.

Related: What Are Big Data Analytics? (Definition, Benefits and Tips)

What is stream processing?

Stream processing is a methodology for managing big data. With stream processing, professionals can continually collect, analyze, filter or transform their data. You may sometimes hear stream processing referred to by a variety of other names, including streaming analytics, event processing, real-time analytics, complex event processing or real-time streaming analytics. When the stream process finishes, professionals can then transfer that data to a data storage system, an application or a different stream processing engine.

How does stream processing work?

Stream processing requires a tool called an event stream processor. This tool can automatically gather data from a designated source in real-time, meaning as the data is generated. The stream processor ca n also, on its own, evaluate the data, transform it into different formats, filter out unnecessary information, scale up to higher volumes of data and deliver its processed data to each application or data storage system in the network.

To use stream processing, professionals can either develop code from start to finish or access an event stream processor. The best option depends on an array of factors, such as the complexity of your data sets, and if you anticipate scaling the data at some point. If you decide to write the code yourself, use a message broker, meaning a programming module that can translate your data into various formats based on how the receiving device processes information. Develop code for this message broker that allows you to receive events from topics in the broker, which can become your data stream.

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What are the benefits of stream processing?

Following are the primary advantages of using stream processing as part of your data management:

  • Manage data continuously: One of the primary benefits of stream processing is that you can continually perform data analytics in real-time. Some other data processing methods require you to temporarily pause your data collection process to analyze each set of information.

  • Filter or clean data easily: Stream processing makes it easier for you to filter or clean your data to reduce the amount of repetitive or unnecessary information. This allows you to only keep the components of your data most relevant for your goal.

  • Boost operational efficiency: When you use stream processing, you're required to conduct fewer data management tasks related to consuming, processing or transforming your data. This can help optimize your company's efficiency.

  • Optimize your organization's plans and decisions: If you're using stream processing to help you evaluate company data, then this data management methodology can improve your organization's decision-making process or strategic plans. For example, you might use stream-processing to analyze in real-time ways to make your business' manufacturing processes more efficient.

  • Improve user experience: Companies that use stream processing for procedures related to their end-users can optimize their user experience. As an example, an organization that develops technology for smart cars can use stream processing to provide drivers with real-time information about their vehicle's performance or efficiency.

  • Enhance data security and reliability: Stream processing can reduce the number of errors that occur during various data management processes, like filtering or transformation. In addition, stream processing tools typically offer your data a secure way to transfer between applications and systems.

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Stream processing vs. batch processing

Batch processing refers to another technique for data management. Here are the principal similarities and differences between the two methodologies:

Pace

Although both batch processing and stream processing can be efficient methods for managing data, stream processing tends to go faster. Batch processing involves periodically stopping data collection so that your data management tools can process and evaluate that data. With stream processing, professionals can continuously gather and analyze data in real-time. While batch processing usually takes some minutes or hours depending on the complexity of the data, stream processing may only need seconds or even milliseconds to collect and analyze data.

Hardware

Batch and stream processing have different hardware requirements. Because batch processing involves managing large chunks of data at various intervals, it typically uses a greater amount of hardware. Since stream processing continually handles smaller amounts of data, professionals can often use less hardware.

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Primary benefits

Both stream and batch processing can offer benefits, depending on what the ultimate purpose is with the data analytics. Batch processing can be a great method for data processing tasks with consistent schedules. For example, you might use batch processing to gather and evaluate metrics for your organization's quarterly report or to calculate how much your hourly wage employees earned last month. In comparison, for data analytics tasks where it's important to evaluate your information in real-time, stream processing may be the better choice.

When to use stream processing

Professionals can use stream processing for an array of reasons, including:

  • Stock market surveillance

  • Smart patient care, such as devices that can track a patient's vitals in real-time

  • Traffic monitoring

  • Social media feeds

  • Sports analytics

  • Geospatial data processing

  • Machine learning maintenance

  • Customer activity or experience

  • Business analytics

  • Location data

  • Smart devices, like cars or homes

  • Immediate marketing or advertising efforts, such as an advertisement for a product similar to the one you just viewed but didn't purchase

  • Algorithmic trading

  • Retail or warehouse inventory management

  • Computer or network monitoring

  • Manufacturing or supply chain analysis

  • Multiplayer games

  • Internet of Things (IoT) analytics

  • Wildlife tracking

  • Fraud detection, such as for credit card scanners that can immediately evaluate potential instances of fraud

  • Surveillance technology, like smart doorbells with video cameras

  • Ride-sharing apps

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Jobs that involve stream processing

An array of jobs and industries can involve stream processing. Here are just a few of the careers you might consider if you want a job where you perform this data management technique:

1. GIS analyst

National average salary: $48,654 per year

Primary duties: A geographic information systems (GIS) analyst collects, analyzes and translates raw geographic data into databases. They typically begin by gathering and organizing geographic information provided by tools such as satellite and remote sensors. A GIS analyst then evaluates and transforms the data to make devices such as GPS systems, digital maps or smartphone apps that use location data.

They perform these tasks by using an array of complex assessment strategies and technologies, such as spatial analysis, which involves evaluating different layers of geographic data from trees to precipitation levels. Some GIS analysts supervise a team of GIS technicians responsible for making the code for geospatial devices. Other job duties include transforming physical maps into digital ones, updating relational databases and analyzing various types of information, like aerial images.

2. Fraud investigator

National average salary: $53,168 per year

Primary duties: A fraud investigator researches, evaluates and follows up on allegations made in relation to potential fraud. They conduct thorough investigations to determine if a particular case represents an actual fraud and to help advise their management team on what steps to take next. The type of fraud that these professionals investigate can vary depending on the company or industry they work in, like law enforcement, the public sector or finance.

Fraud investigators may begin by collecting evidence, such as by interviewing suspects or witnesses, performing background checks or using various fraud analysis methods. They keep detailed documentation throughout this process and use those records and data to write reports for their company leaders. Other responsibilities may include providing expert court testimony, evaluating ways in which their company could improve potential risks related to fraud and collaborating with others such as police officers, bankers or cybersecurity analysts.

3. Marketing specialist

National average salary: $57,680 per year

Primary duties: Marketing specialists create and implement marketing strategies and campaigns. They often begin by conducting thorough research on their target audience, such as what products or services they want and what type of advertising they may respond to positively. A marketing specialist can then develop strategic plans or specific campaigns based on their current departmental goals, whether that's to raise brand awareness, develop audience loyalty, establish their brand's credibility or boost their prospective clients.

A marketing specialist may find full-time employment at a specific company or work as a consultant or through an agency for multiple organizations. Some marketing specialists may focus on one aspect of marketing, such as digital advertising or social media marketing, while others may perform duties in various marketing fields. Specific responsibilities can include generating advertising materials like blog posts or pamphlets, continually tracking data related to their campaign, researching the traits and behaviors of their target audience and collaborating with other marketing professionals.

4. Supply chain analyst

National average salary: $72,172 per year

Primary duties: A supply chain analyst evaluates and extracts meaning from data related to its company's shipping and delivery operations. Their primary goal is typically to optimize the efficiency and quality of all processes related to the organization's supply chain. Supply chain analysts often begin by figuring out the best methods for collecting and processing data related to warehousing, delivery, manufacturing, inventory or scheduling. They can then analyze their accumulated data to find potential areas of improvement.

Although most supply chain analysts find employment opportunities in industries like food and beverage or product manufacturing, some may find jobs elsewhere, such as in technology, packaging or transportation. Other job responsibilities may include negotiating fair prices with vendors or retailers, generating reports for company leaders, developing internal supply chain standards and continually monitoring supply chain data.

5. IoT engineer

National average salary: $125,259 per year

Primary duties: An IoT engineer is a computing professional who specializes in the Internet of Things (IoT), meaning interconnected technologies with sensors, such as smart vacuums or remote health monitoring systems. IoT engineers research, plan, develop and test these types of devices, along with their underlying software or hardware components.

They also frequently test the interconnections between the device they're creating and any systems with which the device communicates. For example, an IoT engineer designing a smart camera for a car makes sure that not only does the camera work but that can integrate seamlessly with the other functions of that vehicle. An IoT engineer's goal is typically to build innovative tech systems that solve their target consumers' challenges or make their lives easier. Other duties can include evaluating end-users' needs, developing platform compatibility with a range of devices and writing code.

6. Network architect

National average salary: $131,556 per year

Primary duties: A network architect develops and maintains an organization's computing network, which may include devices or systems like wide area networks (WANs), wireless adapters and cables. Their primary goal is typically to design and continually support a network structure that's both highly efficient and secure. Some network architects may create smaller networks, like a network connecting two remote worksites, or larger ones, such as a network linked through cloud-supported services.

They might find full-time employment with a specific company or work as a consultant for several businesses. A network architect performs duties such as evaluating a network's potential vulnerabilities, installing new hardware, overseeing network technicians if issues arise and developing the network infrastructure's budget.

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