What Is A Data Processor? (Duties And Differences)

Indeed Editorial Team

Updated 29 September 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.

Companies typically use data to discover how their businesses are progressing, whether their customers are happy and in what ways they can increase profits. Many organisations hire data processors to make the data usable and meaningful. If a career in data processing interests you, knowing what the job involves can help you decide whether this is the right choice for you. In this article, we answer the question 'What is a data processor?', explain their duties and workplaces and describe the differences between a data processor and a data controller.

What Is A Data Processor?

Learning the answer to 'What is a data processor?' can help you understand why companies hire data processors to gain insights into their businesses. A data processor works with organisational and personal data. Personal data includes customer data such as browsing history, buying patterns, location and payment information. Organisational data includes business data such as policies, deals and financial information. A data processor processes all of this data using various tools and techniques to make it usable and enables companies to gather insights from it. Data processors typically work for third-party organisations.

For example, if an e-commerce company selling clothing and accessories wants to learn how to increase its sales, it can examine data on the behaviour of consumers visiting its website. It can then hire a third-party data processing team to process all the consumer data. This team can gather and format the raw data to generate insights on customer browsing habits, shopping carts, checkout times, payment preferences and shopping values. The parent company can then study the structured data to understand customer preferences and devise strategies to better engage with customers.

Related: What Is Data Processing? (With Types, Stages And Uses)

Duties Of A Data Processor

Here are some of the responsibilities of a data processor:

Data preparation

Any raw data that a data controller sends to the data processor is typically in a haphazard format. This means that the data processor's first duty is often data preparation in which they clean and verify the data so that it becomes easier to work on.

The data processor can prepare the data by verifying whether all the information is accurate. They can also evaluate it to check whether any information is missing. If there are any errors in the data, they may rectify or note them. Their job may also involve removing redundancies in the data. They may go through the data to check for relevance and clean it to ensure it follows the main topic or theme of the data set.

Data input

Data processors may require specialised software to interpret the meaning of the data. A data processor typically is familiar with how to use these software tools to process clean data. They usually input the data into the software and then run the code.

This kind of software typically has complex algorithms that can analyse the data and organise it per a company's requirements. The software tools interpret the meaning of the data and return the analysis to the data processor. This output can help the data processor decide the next steps that they may carry out for making the data more meaningful.

Related: Top 20 Big Data Tools: Big Data And Types Of Big Data Jobs

Data organisation

Data processors often use visual aids to interpret the data. Examples include graphs, charts and reports. Data visualisation often helps organisations understand the quantifiable aspects of the data set. For example, a chart may contain a comparison of customer browsing habits over two different quarters of the year to help generate insights about whether seasons affect buyers' decisions. They also may use statistics to organise data. They can use mathematical models, standard deviations and probability to report patterns and variations in the data set.

Related: 11 Data Analysis Tools (Including Tips For Choosing One)

Data storage

Storing data securely is an important duty of a data processor. As the data processing team is typically from a third-party organisation, it becomes more important to store all the data by adhering to the policies and regulations of the company that owns it. It is also important to follow local and national laws for securely accessing, sending, receiving and disposing of data.

Data processors typically store the data in all forms, raw and processed. This is to ensure that all the information is available in case a discrepancy arises. They can store data on systems or use cloud computing. Data processors may use special tools to restrict access to the data and guide the owners of the data on how to safeguard sensitive customer information.

System design

In some cases, highly confidential or sensitive data may require additional layers of security. An example is the credit card information of bank customers. In this case, it may be challenging for data processors to use standard data processing software. Organisations that manage this kind of data may hire more experienced data processors with an additional skill set in computer programming. With proper coding skills, data processors can design custom software with special features that may safeguard highly sensitive information.

Other than security requirements, data sets may also need custom graphs and charts that may not be available in standard software. Data processors with programming skills can customise these standard tools to design modifiable charts which generate additional insights for an organisation.

Intermediary role

Data processors may often work as an intermediary between the owners of the data and the subject of the data. For example, if a retail chain wants to analyse its customer behaviour, it is typically the owner of its customer data. If it collects information about its customers' choices through an analytics website, then the owner of the analytics website becomes the data subject. Data processors can then communicate with both the owners of the e-commerce website and the owners of the analytics website and ensure that the data transfer between all three parties is flawless.

Industries Where Data Processors Work

Data processors work across several industries. With evolving technology, more industries have access to big data. These industries include manufacturing, retail, agriculture, healthcare, finance, technology, human resources and public services. Data processors may work internally for an organisation or a data processing company. If they work internally, they typically focus on one industry, which is the industry in which the company operates. In contrast, if they work for data processing firms, they may work for several industries depending on the firm's client base.

How Are Data Processors Different From Data Controllers?

Here are the differences between data controllers and data processors:

  • Ownership: Data controllers are typically the owners of the data, while data processors process it.

  • Data collection: Data controllers collect the data and provide it to data processors, who generate insights by processing the raw form.

  • Control: Data controllers typically have complete control over the data. They usually decide on the inflow and outflow of data within and outside the organisation, while data processors make the data presentable and valuable.

  • Dual role: In some organisations where budget is a constraint, such as a start-up or where data secrecy is of the utmost importance, such as a government organisation, data controllers may also work as data processors.

  • Internal vs external: In most other industries and bigger companies, data controllers work with a data processing team either internally or outside the organisation. Even when data controllers outsource the data processing tasks to a different team, they usually maintain total control over the data and retain the right to approve all high-level and critical changes to it.

  • Decision-making: Data processors can use tools and techniques to generate insights about a data set and send those insights to the data controller for review. The data controller can then decide how the business can use this information.

  • Security: Data controllers also usually decide the level of security and access control a set of data requires, and data processors can implement those security protocols.

  • Storage: Data controllers can decide the storage duration of data and the ways to dispose of it. They usually instruct the data processors to store and dispose of the data as per the regulations of the company for which the data controller works.

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