The growing volume of data traffic worldwide presents companies with new challenges. They need to store more and more corporate data securely and be able to retrieve it quickly when needed. Data as a Service, a data management strategy based on the cloud, promises to help. We explain what's behind the offer, what advantages it offers you and what you should bear in mind when using Data as a Service.
Definition: What is Data as a Service?
Data as a Service, or DaaS for short, is a model for providing data. This is not stored locally on your on-prem servers, but is stored online in a cloud. DaaS is part of the as-a-service philosophy, which also includes the service models Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).
Data as a Service is similar to the Storage as a Service model. However, DaaS goes a step further by focusing more on analytics tools. In particular, many providers help their customers make data accessible in a structured way. This is crucial because 80 to 90 percent of all corporate data is currently still in unstructured form. This makes it easier to use the possibilities of big data analytics in a way that promotes business.
DaaS models are also becoming more attractive to companies because they can use virtually unlimited resources to store, manage and process their data. Cloud computing providers centrally host DaaS offerings and provide services to their customers on a monthly subscription basis. Billing is usually based on the amount of storage space used.
In addition, Data as a Service is also increasingly used as a business model for selling data. In this case, a data provider makes suitable data sets available to companies from different industries. This data provides the company with new market insights and helps improve products. The data is provided anonymously to meet data protection requirements.
These are the benefits
Data as a Service offers your business a number of key benefits:
High scalability
One major advantage that applies to all as-a-service models is that your services can be scaled up or down at any time, practically without limit. Via the cloud, you can book more storage space with just a few clicks, for example if you need more capacity for seasonal reasons. This gives you the opportunity to respond to changing requirements at any time with full cost control. This also applies in the event that you need to shut down your resource usage again. Thus, your flexibility with a DaaS offering is significantly higher than if you rely on an on-premises solution. The latter first necessitates the purchase of new servers, which may end up going unused.
More innovation
In the digital world, data is the foundation for developing new ideas. For example, predictive analytics can be used to forecast market trends. But data can also tell you how users are using your product, and you can improve your product accordingly. And last but not least, your marketing department can access large amounts of data to monitor website traffic or optimize conversions, for example. With Data as a Service, you can make all this data available to teams in the company. The likelihood of innovation increases because new ideas are successfully implemented more quickly.
High level of structure
You have a much larger amount of data today than you did just a few years ago. The big challenge is to organize these masses of data so that they are easy to access at any time. Data as a Service makes exactly that possible. You can have bundled access to a single version of your data when you need it. Some DaaS providers also provide tools to convert unstructured data into structured formats. This allows you to automatically categorize and search for this data more easily.
Low cost
Data means knowledge - which you can use to make better decisions. This has a positive impact on your costs. Because the fewer bad decisions, the more money you save. What's more: with Data as a Service, you reduce your costs in the area of data management. In a cloud, you generally only pay for exactly those resources that you actually use. This applies in particular to virtual storage space in DaaS solutions.
In addition, you need less personnel. This is because an externally hosted DaaS platform does not draw away employees who have to take care of managing and processing your data. These tasks are the sole responsibility of the service provider. Instead, your IT staff can devote their time to other challenges within the company.
Latest technologies
The success of your data management depends largely on the technologies and tools you use. This includes the timely provision of updates to take advantage of new features and close security gaps. With Data as a Service, you no longer have to worry about these processes. A professional DaaS partner works with the latest tools and automates regular maintenance of its platform. This is essentially in the interest of the service provider, so as not to lose you to a better positioned competitor. You also benefit from the experience of such providers, who implement new technologies for numerous customers in parallel.
High security
In times of increasing cyberattacks, you need to protect your data effectively. Professional DaaS platforms use integrated access control tools - including data encryption and identity and access management. This increases the security of your data and creates the basis for compliance guidelines. The aforementioned automated maintenance of the various software components also helps to ensure that your data is protected against misuse in the best possible way.
The challenges of DaaS
Data as a Service offers you a number of benefits, but also comes with some challenges. We'll explain what those are and what you can do to successfully overcome them in this section.
Data security
In principle, Data as a Service offers you a high level of data security. However, IT security and data protection can also become a challenge if you do not address the issue with a comprehensive strategy and the associated processes.
For one thing, this concerns the use of different end devices. Cloud services are also accessed particularly frequently via smartphone, tablet or private laptop, especially in times of remote work. This creates new gateways for cyber attacks. You should set clear usage guidelines for your employees.
Secondly, you should consider whether all company data can really be migrated to a public cloud or whether particularly sensitive data is better kept in a private cloud. This applies to patient or financial data, for example, which should be specially secured for data protection reasons.
Large volumes of data
When switching to a DaaS solution, you will probably have to transfer large volumes of data. This can take a long time, depending on network bandwidth. In the worst case scenario, this will interrupt critical business processes, resulting in costs or even the loss of customers. It can therefore make a lot of sense to research data compression solutions in advance of the migration.
Such compression methods can also be beneficial for companies that work with large amounts of "hot data," i.e., data that must be retrieved frequently. One tip is to approach potential DaaS providers about this issue in advance, as they often have a lot of compression experience. At the same time, the response of providers can also serve as a selection criterion when choosing a provider.
Limited range of functions
Depending on the DaaS provider, it is possible that not all the tools you prefer for your data processing are available. You can only access those applications that are offered to you on the respective DaaS platform. Therefore, find out in advance which features are provided by each provider. Ask your team which of these features are most important to them.
An elegant solution for benefiting from the full range of functions is to use a multi-cloud. In this, you can combine the clouds of different cloud computing providers, such as Amazon Web Services or Microsoft Azure, and use the services offered in parallel.
Adherence to compliance
When it comes to compliance, the same applies: A cloud environment offers potential and challenges at the same time. This applies in particular to cooperation with providers whose data centers are located outside Europe. Here, it must be checked on a case-by-case basis whether these meet the strict requirements of the GDPR.
A very good solution is to work with a managed services provider (MSP). This "mediates" the offers of large cloud providers by setting them up and managing them for you. Accordingly, he is well versed in compliance issues. Alternatively, a good MSP will also be able to offer you cloud solutions hosted in Germany that meet particularly high security requirements.
Other service models of cloud computing.
In addition to Data as a Service, there are other service models that provide you with resources and services in a cloud. These are the three main ones:
IaaS: Infrastructure as a Service.
With the Infrastructure as a Service (IaaS) model, you can use entire IT infrastructures via the cloud. This primarily includes computing power and network resources. The various components are provided by an IaaS provider. The big advantage is that you can easily scale the scope of the services as required; there is no need for the costly acquisition of your own servers. Maintenance costs are also not incurred. Billing is based on a cost-transparent subscription.
You can use IaaS via public cloud, private cloud or hybrid cloud, depending on your preference. This model is particularly useful if you have widely varying requirements for IT resources. Because of the very good scalability, you can increase and also reduce the scope of use at any time. The big players in IaaS include Microsoft Azure, Amazon Web Services (AWS) and the Google Cloud.
PaaS: Platform as a Service
Platform as a Service (PaaS) is one service level higher than IaaS. PaaS serves as a complete development and deployment environment, building on IaaS services (servers, storage, network elements) to provide access to additional elements such as development tools, databases and middleware.
PaaS makes sense, for example, if you are working with multiple development teams located in geographically diverse locations. This way, each team member can track the changes of the other team members in real time. But PaaS is also well suited for modern development frameworks like Agile and DevOps.
As with IaaS, the scope of PaaS can be scaled at will at any time. In addition, PaaS tools are characterized by their efficient management. Major PaaS providers are Microsoft Azure, AWS, Google Cloud Platform and the IBM Cloud.
SaaS: Software as a Service
The acronym SaaS stands for Software as a Service. The model forms the top level of the service pyramid. Here, an external service provider makes various software solutions available via the Internet. They are usually used directly in the browser. SaaS services are often available in a free basic version, with more advanced functions having to be activated for a fee (freemium model). Well-known SaaS examples in the corporate sector are Microsoft 365 and Microsoft Teams.
A major advantage of SaaS is that it eliminates the need to install software locally. Your employees simply open their browser, log in, and get to work. It also eliminates the need for time-consuming patch management. Both contribute to your IT department being able to focus more on core tasks and innovation processes.
Best practices for successful data management
To implement successful data management in the cloud, you should consider certain best practices.
1. sensitize employees
Make your employees aware of the data culture in your company. Make it clear how important the maintenance, proper storage and security of your data are for a smooth workflow and the success of your company. To get this across, you can hold regular training sessions on data management, for example. Because you can only fully exploit the potential of professional data management if you "take your entire team with you".
2. define guidelines for file naming
If you want to use data, you have to be able to find it. Therefore, create guidelines for your employees to use when naming and cataloging data. Use standardized file names for this purpose. For example, you could use a date format such as YYYY-MM-DD, in conjunction with uniformly defined project names. Regardless of the format you choose, it is important that the system is known to all people involved. You can achieve this through central knowledge management in the company.
3. maintain metadata
It is also important to ensure the traceability of all activities related to a file. To achieve this, metadata must be carefully maintained. Among other things, they contain information about who created a file, which other people edited it, and when the various activities took place. This ensures that you can still assign data to its creators and obtain additional information even years later. Maintaining metadata also makes an important contribution to establishing reliable data governance in the company.
4. check data relevance
Regularly check if all your data is still relevant and remove those you no longer need. In the worst case, outdated data can lead to errors in automation processes and documentation. It also ensures that you're not paying for more storage with your DaaS provider than you actually need. For these reasons, regular "housecleaning" should be an integral part of your data management strategy.
5. Ensure data protection
Establish clear data protection standards to prevent improper processing of personal data. Since the GDPR came into effect in 2018, penalties of up to 20 million euros or up to 4 percent of global turnover have been envisaged here in the event of violations. In addition, such breaches are accompanied by major losses of trust among stakeholders.
In the DaaS sector, it is particularly important to pay attention to the country in which the respective provider's data centers are located. If the data is stored in a non-European country, there is a high probability that the GDPR requirements will not be met. In any case, carry out a check in advance.
However, data protection requirements must also be taken into account when processing data internally. In fact, most procedural errors occur in-house. Therefore, you should not only keep an eye on the data of customers and partners, but also on the personal data of your employees.
6. Consider Managed Services
Consider working with a managed services provider (MSP). These specialized providers act as "intermediaries" between you and the major DaaS providers. To do this, the MSP first performs an individual assessment of your existing infrastructure and then designs a custom-fit solution for you. The MSP also takes care of the complete implementation and ongoing maintenance.
The high degree of personalization is particularly noticeable when it comes to support. Whereas with large providers you often have to deal with changing people, MSPs attach importance to having a constant contact person. This allows a personal relationship to be built up, which is a big plus for many medium-sized customers in particular.
Definition: What is Data as a Service?
Data as a Service, or DaaS for short, is a model for providing data. This is not stored locally on your on-prem servers, but is stored online in a cloud. DaaS is part of the as-a-service philosophy, which also includes the service models Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).
Data as a Service is similar to the Storage as a Service model. However, DaaS goes a step further by focusing more on analytics tools. In particular, many providers help their customers make data accessible in a structured way. This is crucial because 80 to 90 percent of all corporate data is currently still in unstructured form. This makes it easier to use the possibilities of big data analytics in a way that promotes business.
DaaS models are also becoming more attractive to companies because they can use virtually unlimited resources to store, manage and process their data. Cloud computing providers centrally host DaaS offerings and provide services to their customers on a monthly subscription basis. Billing is usually based on the amount of storage space used.
In addition, Data as a Service is also increasingly used as a business model for selling data. In this case, a data provider makes suitable data sets available to companies from different industries. This data provides the company with new market insights and helps improve products. The data is provided anonymously to meet data protection requirements.
These are the benefits
Data as a Service offers your business a number of key benefits:
High scalability
One major advantage that applies to all as-a-service models is that your services can be scaled up or down at any time, practically without limit. Via the cloud, you can book more storage space with just a few clicks, for example if you need more capacity for seasonal reasons. This gives you the opportunity to respond to changing requirements at any time with full cost control. This also applies in the event that you need to shut down your resource usage again. Thus, your flexibility with a DaaS offering is significantly higher than if you rely on an on-premises solution. The latter first necessitates the purchase of new servers, which may end up going unused.
More innovation
In the digital world, data is the foundation for developing new ideas. For example, predictive analytics can be used to forecast market trends. But data can also tell you how users are using your product, and you can improve your product accordingly. And last but not least, your marketing department can access large amounts of data to monitor website traffic or optimize conversions, for example. With Data as a Service, you can make all this data available to teams in the company. The likelihood of innovation increases because new ideas are successfully implemented more quickly.
High level of structure
You have a much larger amount of data today than you did just a few years ago. The big challenge is to organize these masses of data so that they are easy to access at any time. Data as a Service makes exactly that possible. You can have bundled access to a single version of your data when you need it. Some DaaS providers also provide tools to convert unstructured data into structured formats. This allows you to automatically categorize and search for this data more easily.
Low cost
Data means knowledge - which you can use to make better decisions. This has a positive impact on your costs. Because the fewer bad decisions, the more money you save. What's more: with Data as a Service, you reduce your costs in the area of data management. In a cloud, you generally only pay for exactly those resources that you actually use. This applies in particular to virtual storage space in DaaS solutions.
In addition, you need less personnel. This is because an externally hosted DaaS platform does not draw away employees who have to take care of managing and processing your data. These tasks are the sole responsibility of the service provider. Instead, your IT staff can devote their time to other challenges within the company.
Latest technologies
The success of your data management depends largely on the technologies and tools you use. This includes the timely provision of updates to take advantage of new features and close security gaps. With Data as a Service, you no longer have to worry about these processes. A professional DaaS partner works with the latest tools and automates regular maintenance of its platform. This is essentially in the interest of the service provider, so as not to lose you to a better positioned competitor. You also benefit from the experience of such providers, who implement new technologies for numerous customers in parallel.
High security
In times of increasing cyberattacks, you need to protect your data effectively. Professional DaaS platforms use integrated access control tools - including data encryption and identity and access management. This increases the security of your data and creates the basis for compliance guidelines. The aforementioned automated maintenance of the various software components also helps to ensure that your data is protected against misuse in the best possible way.
The challenges of DaaS
Data as a Service offers you a number of benefits, but also comes with some challenges. We'll explain what those are and what you can do to successfully overcome them in this section.
Data security
In principle, Data as a Service offers you a high level of data security. However, IT security and data protection can also become a challenge if you do not address the issue with a comprehensive strategy and the associated processes.
For one thing, this concerns the use of different end devices. Cloud services are also accessed particularly frequently via smartphone, tablet or private laptop, especially in times of remote work. This creates new gateways for cyber attacks. You should set clear usage guidelines for your employees.
Secondly, you should consider whether all company data can really be migrated to a public cloud or whether particularly sensitive data is better kept in a private cloud. This applies to patient or financial data, for example, which should be specially secured for data protection reasons.
Large volumes of data
When switching to a DaaS solution, you will probably have to transfer large volumes of data. This can take a long time, depending on network bandwidth. In the worst case scenario, this will interrupt critical business processes, resulting in costs or even the loss of customers. It can therefore make a lot of sense to research data compression solutions in advance of the migration.
Such compression methods can also be beneficial for companies that work with large amounts of "hot data," i.e., data that must be retrieved frequently. One tip is to approach potential DaaS providers about this issue in advance, as they often have a lot of compression experience. At the same time, the response of providers can also serve as a selection criterion when choosing a provider.
Limited range of functions
Depending on the DaaS provider, it is possible that not all the tools you prefer for your data processing are available. You can only access those applications that are offered to you on the respective DaaS platform. Therefore, find out in advance which features are provided by each provider. Ask your team which of these features are most important to them.
An elegant solution for benefiting from the full range of functions is to use a multi-cloud. In this, you can combine the clouds of different cloud computing providers, such as Amazon Web Services or Microsoft Azure, and use the services offered in parallel.
Adherence to compliance
When it comes to compliance, the same applies: A cloud environment offers potential and challenges at the same time. This applies in particular to cooperation with providers whose data centers are located outside Europe. Here, it must be checked on a case-by-case basis whether these meet the strict requirements of the GDPR.
A very good solution is to work with a managed services provider (MSP). This "mediates" the offers of large cloud providers by setting them up and managing them for you. Accordingly, he is well versed in compliance issues. Alternatively, a good MSP will also be able to offer you cloud solutions hosted in Germany that meet particularly high security requirements.
Other service models of cloud computing.
In addition to Data as a Service, there are other service models that provide you with resources and services in a cloud. These are the three main ones:
IaaS: Infrastructure as a Service.
With the Infrastructure as a Service (IaaS) model, you can use entire IT infrastructures via the cloud. This primarily includes computing power and network resources. The various components are provided by an IaaS provider. The big advantage is that you can easily scale the scope of the services as required; there is no need for the costly acquisition of your own servers. Maintenance costs are also not incurred. Billing is based on a cost-transparent subscription.
You can use IaaS via public cloud, private cloud or hybrid cloud, depending on your preference. This model is particularly useful if you have widely varying requirements for IT resources. Because of the very good scalability, you can increase and also reduce the scope of use at any time. The big players in IaaS include Microsoft Azure, Amazon Web Services (AWS) and the Google Cloud.
PaaS: Platform as a Service
Platform as a Service (PaaS) is one service level higher than IaaS. PaaS serves as a complete development and deployment environment, building on IaaS services (servers, storage, network elements) to provide access to additional elements such as development tools, databases and middleware.
PaaS makes sense, for example, if you are working with multiple development teams located in geographically diverse locations. This way, each team member can track the changes of the other team members in real time. But PaaS is also well suited for modern development frameworks like Agile and DevOps.
As with IaaS, the scope of PaaS can be scaled at will at any time. In addition, PaaS tools are characterized by their efficient management. Major PaaS providers are Microsoft Azure, AWS, Google Cloud Platform and the IBM Cloud.
SaaS: Software as a Service
The acronym SaaS stands for Software as a Service. The model forms the top level of the service pyramid. Here, an external service provider makes various software solutions available via the Internet. They are usually used directly in the browser. SaaS services are often available in a free basic version, with more advanced functions having to be activated for a fee (freemium model). Well-known SaaS examples in the corporate sector are Microsoft 365 and Microsoft Teams.
A major advantage of SaaS is that it eliminates the need to install software locally. Your employees simply open their browser, log in, and get to work. It also eliminates the need for time-consuming patch management. Both contribute to your IT department being able to focus more on core tasks and innovation processes.
Best practices for successful data management
To implement successful data management in the cloud, you should consider certain best practices.
1. sensitize employees
Make your employees aware of the data culture in your company. Make it clear how important the maintenance, proper storage and security of your data are for a smooth workflow and the success of your company. To get this across, you can hold regular training sessions on data management, for example. Because you can only fully exploit the potential of professional data management if you "take your entire team with you".
2. define guidelines for file naming
If you want to use data, you have to be able to find it. Therefore, create guidelines for your employees to use when naming and cataloging data. Use standardized file names for this purpose. For example, you could use a date format such as YYYY-MM-DD, in conjunction with uniformly defined project names. Regardless of the format you choose, it is important that the system is known to all people involved. You can achieve this through central knowledge management in the company.
3. maintain metadata
It is also important to ensure the traceability of all activities related to a file. To achieve this, metadata must be carefully maintained. Among other things, they contain information about who created a file, which other people edited it, and when the various activities took place. This ensures that you can still assign data to its creators and obtain additional information even years later. Maintaining metadata also makes an important contribution to establishing reliable data governance in the company.
4. check data relevance
Regularly check if all your data is still relevant and remove those you no longer need. In the worst case, outdated data can lead to errors in automation processes and documentation. It also ensures that you're not paying for more storage with your DaaS provider than you actually need. For these reasons, regular "housecleaning" should be an integral part of your data management strategy.
5. Ensure data protection
Establish clear data protection standards to prevent improper processing of personal data. Since the GDPR came into effect in 2018, penalties of up to 20 million euros or up to 4 percent of global turnover have been envisaged here in the event of violations. In addition, such breaches are accompanied by major losses of trust among stakeholders.
In the DaaS sector, it is particularly important to pay attention to the country in which the respective provider's data centers are located. If the data is stored in a non-European country, there is a high probability that the GDPR requirements will not be met. In any case, carry out a check in advance.
However, data protection requirements must also be taken into account when processing data internally. In fact, most procedural errors occur in-house. Therefore, you should not only keep an eye on the data of customers and partners, but also on the personal data of your employees.
6. Consider Managed Services
Consider working with a managed services provider (MSP). These specialized providers act as "intermediaries" between you and the major DaaS providers. To do this, the MSP first performs an individual assessment of your existing infrastructure and then designs a custom-fit solution for you. The MSP also takes care of the complete implementation and ongoing maintenance.
The high degree of personalization is particularly noticeable when it comes to support. Whereas with large providers you often have to deal with changing people, MSPs attach importance to having a constant contact person. This allows a personal relationship to be built up, which is a big plus for many medium-sized customers in particular.