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Like all traditional members of the “as-a-Service” family such, Data-as-a-Service is a relatively new term, as it is being used since 2015. The purpose of DaaS is that it delivers data on demand to the consumers through various APIs in order to avoid the typical need to fetch as well as store large data assets and then search for the required information in the data asset.
This open source software solution basically runs between the systems which manage your data and the tools which you use for analysing the data. This service can be used in various sectors such as retail, healthcare, e-commerce, financial sectors, telecommunications, homeland security, organisations, etc. where the users can be able to access the databases provided by the vendors or host their own databases on their self-managed systems. It is a self-service model where you can explore, organise, describe as well as analyse data regardless of its location, size or structure with the help of tools such as Tableau, Python, etc.
According to a report by Telecommunications Market Research Reports, the future revenue from big data-driven telecom analytics and Data-as-a-service to grow big data revenue into $5.4 billion industry by 2019. The telecom analytics market alone is expected to grow at a compound annual growth rate of nearly 50% between 2014 and 2019.
This alternative cloud computing service model is different from the traditional as-a-service models. Organisations have been struggling with the data lakes (cloud storage services) since the last few years due to the heavy flow of data and unavailability of the right tools.
This open source software solution basically runs between the systems which manage your data and the tools which you use for analysing the data. This service can be used in various sectors such as retail, healthcare, e-commerce, financial sectors, telecommunications, homeland security, organisations, etc. where the users can be able to access the databases provided by the vendors or host their own databases on their self-managed systems. It is a self-service model where you can explore, organise, describe as well as analyse data regardless of its location, size or structure with the help of tools such as Tableau, Python, etc.
According to a report by Telecommunications Market Research Reports, the future revenue from big data-driven telecom analytics and Data-as-a-service to grow big data revenue into $5.4 billion industry by 2019. The telecom analytics market alone is expected to grow at a compound annual growth rate of nearly 50% between 2014 and 2019.
This alternative cloud computing service model is different from the traditional as-a-service models. Organisations have been struggling with the data lakes (cloud storage services) since the last few years due to the heavy flow of data and unavailability of the right tools.
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