Have you’ve been hearing about the term Big Data, but you are not quite sure what it is? Eminence, your digital marketing agency will provide you with a simple explanation of the concept.
Big Data is a term that refers to the very large amount of data that circulates daily and that companies receive and must process. The challenges of correctly processing this data are both commercial and marketing related. Although there are many benefits to processing and transforming data into valuable information.
In order to better understand this concept, there are the 3 Vs (Volume, Velocity and Variety) that are used to describe it. If you wish to define Big Data in even more detail, there are the following 5 Vs to take into consideration:
- Volume: this refers to the very large amount of data generated every second from many sources, such as business transactions, social networks and sensors of connected objects or geolocation for example.
- Velocity: this corresponds to the speed of data creation, but also to the speed at which data flows circulate, as well as the analysis of this data in real time.
- Variety: refers to the type of data analysed. The different types of formats include:
- Structured data: is related to specific information located in a fixed field and in a predetermined format that allows machines to interpret and process it, i.e. a spread sheet or database. This makes it possible to retrieve information such as customer data, transaction data, financial data or data related to the number of visits to a website.
- Unstructured data: this refers to all the other data that is not organized in databases or that cannot be easily interpreted. For example, email or conversations on social networks, videos or images, GPS location data.
- Semi-structured data: is a combination of structured and unstructured data. This means that, although the data is not structured or organized in databases or spread sheets, it is still associated with certain information, such as tags, which enables the data to be analysed.
- Veracity: in order to be able to use data effectively, a company must be confident that it can trust it. Indeed, if the quality and accuracy of the data is not reliable, it could create a snowball effect (e. g. a user who puts an incorrect name) causing many other problems related to the repetition of the error in question. Therefore, it is essential that the information used is filtered, purified and consistent so that companies can make the right decisions.
- Value: Data is only useful if it generates value, which is why Big Data Analytics helps companies to exploit information to extract something valuable and thus facilitate the identification of new opportunities. Indeed, it allows companies to achieve smarter actions and more efficient operations, thus generating more generous profits whilst satisfying customers.
What are the advantages of this practice?
You probably already know this already but, if companies use Big Data so much it must be because it has more than one advantage:
- Improve decision-making: with Big Data, it is possible to get more insight into consumers’ interests and desires, their habits, and their feelings about specific products and services. This information can therefore be used to make better decisions across all sectors of a business.
- Improve operations: it also allows a company to improve the efficiency of its operations as well as its internal operations. This is made possible mainly through the data collected from connected devices, thus providing additional information, such as the performance of a machine or the level of stress or health of an employee, for example.
- Monetize data: when a company produces data and therefore owns it, it can sell it to a third party and get financial value from it. In the field of marketing, this practice is most often carried out during the monetization of personal data, consisting of selling – with authorization of transmission – to a third person, the data of customers or prospects.
Are there any risks to consider?
Alas, every rose has its thorn, and in this case, you should definitely be careful when it comes to Big Data. Here are some important points to keep in mind:
- Data security: data theft is becoming more and more frequent. The more important and valuable the data is, the bigger target it becomes.
- Data privacy: companies must be able to ensure that the information collected will not be misused or mistakenly disclosed by those responsible for processing it. If it is indeed misused, the company in question could be exposed to costly lawsuits and its overall reputation could be jeopardized.
- Bad Data: companies may collect data that is irrelevant, out-dated or even false. This is often due to insufficient time spent preparing the project strategy.
- Incorrect analysis of the collected data: the use of the gathered data is not done in a straightforward way. In order to be able to draw something from it, it is necessary to analyse the data first. However, it is important not to draw causal links without an in-depth analysis of the data beforehand. If this were the case, the results of this analysis could lead to a hasty and incorrect conclusion, or to draw connexions between data when in reality it is only a coincidence.