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The basics of data processing


A brief intro to data processing

Whether you are just starting out or have been in business for years, understanding the basics of data processing is of the utmost importance. Technology is shaping the way in which business is done and remaining informed on the latest developments is what helps businesses remain competitive. This article explores the basics, giving you a ‘bitesize’ introduction to the concept of data processing.   

The intended audience of this article is not the seasoned privacy professionals that have been working with data protection for years. This article is for the organisations that are about to initiate their data protection journey – either because they are newly established or operating in jurisdictions where data protection requirements are just being introduced.  

What is data processing?

One concept that everyone relying on personal data to manage their business needs to understand, is “what is data processing”. To put it simply, data processing consists of the collection and translation of data into usable information. As will be considered below, processing data can offer valuable insight to businesses of all types and sizes.  

How is data processed?

Several stages are involved in processing data prior to it becoming usable by employees in all areas of a business. Starting as raw data and ending up as more useful outputs, each stage will be explored in brief below.  

Stage 1: Collecting data

The first stage corresponds to the actual collection of data. A variety of sources may be used in order to acquire such data and it is imperative to rely upon good sources of data. Utilising outdated or low-quality data from a secondary source may lead to inaccurate results which could cost your business.  

From a data protection perspective, the one important thing you need to consider with regards to collection of data, is whether you have the right to do so. This is also referred to as the legal basis, and it may vary depending on the circumstances under which you collect the data. You may for example be required to collect an explicit consent from the person you are collecting data on, but other times you can rely on the contract you have or simply a legal obligation.  

Stage 2: Preparing data

Once the data has been collected, the next part of the processing will take place. In this stage the data is prepared for use. This preparation should include organising the data and reviewing it for any errors, being sure to fix errors if they exist. This stage can be regarded as a sort of ‘quality assurance’ stage ensuring that in the following stages you will be using the most accurate data possible.  

Stage 3: Storing data

Once the preparation stage is complete, the data can be entered into its ultimate place of storage. Data may be stored in data warehouses or alternative forms of databases. It is following this stage that the data will begin being translated into more legible content.  

Stage 4: Interpreting data

With the help of various algorithms, the collected and stored data can be analysed and interpreted. This may occur via different methods depending on the origin of the data as well as the final desired use of it. It is important that the correct type of processing be used for a given data collection to permit accurate and valid interpretations thereafter. After analysis, the data will be translated into a more readable output format and can be displayed in a useful form such as documents, graphs, and charts.  

Stage 5: Deletion of data

Once the collected data has been used for the collected purpose and is no longer relevant to store, the data should be deleted. The retention time and limits will vary greatly from data type to data type and the different purposes for which the data has been collected. This should be structured in a retention schedule, so that the organisation knows when to purge outdated and irrelevant data from its information assets.  

It is important to emphasise that all 5 stages constitute processing, cf. e.g. GDPR art. 4.1(2). Therefore, all stages will be subject to data protection requirements and will need to be managed accordingly to ensure compliance.  

Considerations when using data

There are a number of critical considerations that a business will have to review when processing data. Below we explore a few key issues that organisations will need to consider when using data for business purposes.  

Bias is one of biggest issues businesses face. Biases in data can take form in numerous ways and can impact the usefulness of the resulting information arising out of it. For example, a company may encounter an omitted variable bias which results when important pieces of information are missing or left out. It is important to evaluate the data sources a business chooses to rely on, to ensure data inputs are of the most reliable and highest quality possible from the get-go. It also of key importance to consider how well the sampled data represents the greater population from which it was drawn. For example, biases may arise in online reviews as typically the people who leave reviews are not representative of everyone’s opinions. Although in some situations drawing from a larger pool of data may help to avoid this issue, this is not always true. Businesses must determine who they are trying to represent with the results from processing such data and ensure they utilise data which will accurately depict this group.   

Another hurdle businesses may face amid processing data relates to the motivation for processing the data in the first place. It is important to not jump into action prior to carrying out consideration as to why data needs to be processed. Businesses should evaluate their reasons and needs for processing data. The act of processing data generally should be regarded as a fact-finding process which is forward looking. In contrast, utilising data to justify a past decision should be avoided. For example, a company may gather data to determine which product is the most profitable. Rather than processing data to try and justify the introduction of the latest product into the company, the company should seek to collect data on multiple products which it can compare to determine the most profitable product.  

Technology presents another hurdle which businesses commonly experience in the course of processing data. The highest quality data is typically the most difficult to obtain. This can be, for example, due to the costs associated with obtaining such data. Thus, businesses must consider any cost constraints they face and meticulously develop a budget to allocate resources specifically to data processing. Prior to selecting technology for processing data, businesses should consider their need for and intended uses of the data in order to select the best suited data processing technologies. For example, a business that processes a large amount of data and is a part of a large group of entities may choose to use stream analytics software. This software allows businesses to more easily analyse data from external data sources due to its integration powers making it easier for data to be accessed within a group.  

Although there are several hurdles that businesses may face, there are several benefits associated with data processing that should be considered when deciding to process data. We will explore these benefits below.  

The benefits of effective data processing

After developing a basic understanding of what data processing is and how it can be carried out, businesses may be wondering why they should consider processing data in the first place. Despite the hurdles that businesses may face at first when processing data, the benefits of doing so are typically far greater than not studying data. At a minimum the outcome of processing raw data gives businesses important information which they can harness to make more informed business decisions; however, there are numerous other benefits businesses can receive. The opportunities are wide-ranging and below we explore only a select few reasons as to why businesses should consider processing data.  

Data processing can be used to increase for example the efficiency of recruitment processes. By processing data, businesses can more easily compare candidates applying for a position allowing them to determine which candidate is right for the business. It can also be helpful in analysing employees by reviewing their strengths and weakness allowing businesses to better organise their work departments and task assignments.  

Processing data can help businesses better understand their existing customers by tracking and predicting customer behaviour. For example, the marketing department can track the effectiveness of certain marketing strategies and the impact they have on influencing customer purchases. Additionally, it allows businesses to better evaluate and categorise customers allowing them to provide their customers with greater value by targeting their direct needs or interests.  

Data processing can also promote the use of efficient business processes. For example, businesses may consider tracking the quality of products or services they offer, tracking the performance of employees or suppliers, or considering the risks the business faces.  

On a higher level, processing data can assist businesses in remaining competitive. Whether using data to review your competitors’ offers and products, or discerning market trends, processing data can contribute to the longevity of a business.   

Though not exhaustive, the above begins to describe how processing data can be useful to your business. The other side of the coin is of course, that once you start to process data, you will be subject to data protection regulation and there will be a number of requirements you will need to consider and comply with.  


In conclusion, the benefits arising from processing data are endless. As the use of technology in a commercial context becomes more prevalent businesses need to get more creative to survive. Processing data can be the key to understanding your business and remaining relevant in the challenging commercial landscape of the 21st century.  

Before commencing with processing data, it is advisable to brainstorm three key things.   

  1. Why do you want to process data?  
  1. How will you process data?  
  1. What legislation must be complied with?  

If you want to begin processing data or already do and need insight on the possible legal implications of data processing, do not hesitate to contact us. We are always happy to help you in any way we can.  



Bem. (2021, June 10). 5 uses of Big Data Analytics in business process management – bem. Business Enterprise Mapping. Retrieved November 8, 2021, from

Data Culture Toolkit: Barriers to Data Use. Dasy . (2021, April 16). Retrieved November 21, 2021, from

What is Data Processing? definition and stages – talend cloud integration. Talend. (n.d.). Retrieved November 21, 2021, from

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