Business intelligence – are all business data valuable?
‘The business model of internet giants such as Google and Facebook is based largely on data. By this point, we all understand how valuable data are – customer data are indispensable for business operations for example. They obviously represent financial value.’
‘At the point of creation, it is not always obvious what types of business data are valuable. Often, it takes time for the value of certain data to become apparent – for your own business and maybe even for customers, suppliers and other parties.’
‘Such data might include production logs with data on machine performance on the shop floor. Over time, these data might be of interest to the producer as part of R&D for innovation and optimisation. It’s important that they aren’t just discarded.’
‘Another example is tracking data and phone logs for mobile phone subscribers. Historically, the value of these data has not always been recognised. Today, one particular Belgian mobile phone operator sells the anonymised data to cities and towns, which use the information for urban market research and security policies. Or look at Tesla, which collects data from all of its cars. The data are then used to build the AI that makes self-driving cars possible. Your fleet can produce valuable data.’
Storage costs
‘Data may represent a financial value, but there are costs as well. Because of high storage costs, data were once deleted after a period of time. Today, storage costs are much lower and you can easily park your structured and unstructured data in a data lake. Storage is available for all types of data volume, and depending on what sort of accessibility you need, you can opt for cold, warm or hot storage.’
Processing costs
‘To be able to take full advantage of data, you need to know precisely what you are storing. You can do this by assigning technical and functional metadata to the data. There are other considerations when it comes to investing in data processing. Sensitive or confidential data need to be secured. Other data require less protection. Some data types are subject to legal requirements, such as privacy, availability and retrievability requirements. Data asset management clarifies who is responsible and who has access. These features are an essential part of the decision-making process.’
Anticipate the future value of data
‘Data are quietly evolving from a means to an end to something with intrinsic value and over time, could become an asset on the balance sheet. By investing in the quality of data, you can even make data marketable. Many companies are not at that stage yet, but the evolution has nevertheless begun. With the right data strategy in place, you can secure your data and ensure that they are processed appropriately. That way, you can anticipate the future value of business data.’
‘The business model of internet giants such as Google and Facebook is based largely on data. By this point, we all understand how valuable data are – customer data are indispensable for business operations for example. They obviously represent financial value.’
‘At the point of creation, it is not always obvious what types of business data are valuable. Often, it takes time for the value of certain data to become apparent – for your own business and maybe even for customers, suppliers and other parties.’
‘Such data might include production logs with data on machine performance on the shop floor. Over time, these data might be of interest to the producer as part of R&D for innovation and optimisation. It’s important that they aren’t just discarded.’
‘Another example is tracking data and phone logs for mobile phone subscribers. Historically, the value of these data has not always been recognised. Today, one particular Belgian mobile phone operator sells the anonymised data to cities and towns, which use the information for urban market research and security policies. Or look at Tesla, which collects data from all of its cars. The data are then used to build the AI that makes self-driving cars possible. Your fleet can produce valuable data.’
Storage costs
‘Data may represent a financial value, but there are costs as well. Because of high storage costs, data were once deleted after a period of time. Today, storage costs are much lower and you can easily park your structured and unstructured data in a data lake. Storage is available for all types of data volume, and depending on what sort of accessibility you need, you can opt for cold, warm or hot storage.’
Processing costs
‘To be able to take full advantage of data, you need to know precisely what you are storing. You can do this by assigning technical and functional metadata to the data. There are other considerations when it comes to investing in data processing. Sensitive or confidential data need to be secured. Other data require less protection. Some data types are subject to legal requirements, such as privacy, availability and retrievability requirements. Data asset management clarifies who is responsible and who has access. These features are an essential part of the decision-making process.’
Anticipate the future value of data
‘Data are quietly evolving from a means to an end to something with intrinsic value and over time, could become an asset on the balance sheet. By investing in the quality of data, you can even make data marketable. Many companies are not at that stage yet, but the evolution has nevertheless begun. With the right data strategy in place, you can secure your data and ensure that they are processed appropriately. That way, you can anticipate the future value of business data.’