Data Variety: Analysing data structure & types and what they mean to digital marketers?

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Data comes in a variety of different forms and from a variety of different sources. These can be in various different forms, from simple files of text and number to emails, images, audio, PDFs, wearable devices and everything in between. The organisation and storage of these different types of data is what will be discussed in this blog post. Firstly, we have to identify and group data into three categories: Structured data, semi-structured data and unstructured data.

Structured data is data that has been collected and organised in a purposeful manner. It is often stored in a databased management system, which arranges this data into rows which depending on what metric the data is being used for (i.e. age, gender etc). As Bernard Marr states “This makes structured data easy to store, analyse and search and until recently was the only data easily usable for businesses.” (Marr, 2021). However, this in turn makes the data less pliable, meaning that if the business wishes to change the metric being studied, the data must be reprocessed.

Unstructured data is data that is stored in the form of files and is not processed in any way. It is unorganised, full of irrelevant information and would need to be processed in some manner to become useful to a business. Data controllers can begin this process by adding tags to the data or classifying the data, for example, to aid a business needs. This type of data is easily the most common with 80% of business’ data being unstructured. Until recently this type of data was deemed relatively useless to businesses, however recent development of artificial intelligence has “elevated unstructured data to an extremely valuable resource for organisations.” (Marr, 2021).

Semi structured data is data that has elements of both above data types. While it is processed and filed in an orderly manner, it does not have the rigidity of structured data. It is considered to have a self evident structure, meaning the data can be grouped focusing on different elements and attributes of data. This makes the data more flexible and easier to grow as the business grows. The main downside to the use of this data is that it can make analytics difficult as the analysis platform may find the attributes that the data is grouped in difficult to predict.

AWS explains these concept simply as “structured data is hot, immediately ready to be analysed. Semi structured data is lukewarm-some data will be ready to go and other data may need to be cleaned or preprocessed. Unstructured data is the frozen ocean-full of exactly what you need but separated by all kinds of stuff you don’t need.” (AWS, no date).

In conclusion, there are different ways and methods to store and organise a company’s data. A business must try and choose the best system for their needs and the most efficient way of harnessing this data for their marketing and operational requirements. Whether your business is a SME or a global conglomerate, identifying the correct data structure is critical for your marketing needs and the relationship with your customers.

 

James

 

#SME #digitalmarketing #datastructure #datatypes #businesssolutions


References

Marr, B., 2021. What’s The Difference Between Structured, Semi-Structured And Unstructured Data?. [online] Forbes. Available at: <https://www.forbes.com/sites/bernardmarr/2019/10/18/whats-the-difference-between-structured-semi-structured-and-unstructured-data/?sh=181f2dae2b4d> [Accessed 11 March 2021].

 https://www.aws.training/. 2021. [online] Available at: <https://content.aws.training/wbt/danfun/en/x1/1.1.1/index.html?endpoint=https%3a%2f%2flrs.aws.training%2fTCAPI%2f&auth=Basic%20OmYwZTFlZjg1LWJhNTItNDJhMS05MDFmLTVkYzUzYWY2MTk3MQ%3d%3d&actor=%7b%22objectType%22%3a%22Agent%22%2c%22name%22%3a%5b%22wMPGimzgXE-2Zcdd5m_LZA2%22%5d%2c%22mbox%22%3a%5b%22mailto%3alms-user-wMPGimzgXE-2Zcdd5m_LZA2%40amazon.com%22%5d%7d&registration=85e02513-ffc9-4b46-a3ba-3a6c5af0b2b5&activity_id=http%3a%2f%2fj_bvR-AyYKi4T-Ah6n8otLWVG_tcsFET_rise&grouping=http%3a%2f%2fj_bvR-AyYKi4T-Ah6n8otLWVG_tcsFET_rise&content_token=2f156d37-95bc-4ca5-9eb9-caae3e7fd7e7&content_endpoint=https%3a%2f%2flrs.aws.training%2fTCAPI%2fcontent%2f&externalRegistration=CompletionThresholdPercent%7c100!InstanceId%7c0!PackageId%7cdanfun_en_x1_1.1.1!RegistrationTimestampTicks%7c16140838057691543!SaveCompletion%7c1!TranscriptId%7c_o4zLcgjbUqRsjdTIcwySQ2!UserId%7cwMPGimzgXE-2Zcdd5m_LZA2&externalConfiguration=&width=988&height=824&left=274&top=0&width=988&height=824&left=274&top=0#/lessons/9en1mslGAs2-t8qPF-0GXpTW_dt9_Sn1> [Accessed 11 March 2021].


Comments

  1. Natassya Coelho14 March 2021 at 14:04

    Variety is considered one of the 3 V's of Big Data, and it plays an important role. As well explained by James, variety comes in different forms and it refers to collecting data from different sources. It enables a better understanding of information and helps to a more informed decision when utilized appropriately. Clear, uncomplicated access to an extensive variety of data is also the key to creating platforms that boost innovation and efficiency. I completely agree when you state that good structure data is critical for business and it is what the companies should start to do right now. Organising data to build a relationship with consumers.
    Thank you for your content, James.

    ReplyDelete
  2. Udit Shokeen13 April 2021 at 15:38

    This comment has been removed by a blog administrator.

    ReplyDelete
  3. Udit Shokeen15 April 2021 at 14:16

    Thanks James for shedding light on data variety, it was exciting to know how data structure can even affect the marketing of a firm and it’s CRM. Big Data was once mainly used by large corporations because they were the only ones that could afford the technologies and networks used to capture and analyze data. Also small companies will benefit from Big Data and Data Science today by selecting the relevant information for their unique needs and selecting resources or teams that can be accessed remotely and on demand. Big data will assist SMEs in anticipating the tastes and desires of their target audience and customers. Simply put, small businesses must seriously consider big data adoption.

    ReplyDelete

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