Data as a Service – or DaaS – is growing rapidly. In 2015, the global DaaS market was estimated to be worth $1.8bn, with experts predicting a further rise of $6.2bn before 2020. Impressive numbers, certainly, and figures which explain why DaaS has got so many people hot under the collar.
Do we need help to make sense of data?
The idea is an exciting one; that a third-party organization can give you the tools required to make a serious splash with data, and can help your company become data-driven. But are these Data as a Service providers really worth the money? Wouldn’t organizations be better served mining their own data and handling it all in-house?
Let’s take a closer look.
What is Data as a Service?
To start with, we need some definitions. Basically, the term ‘Data as a Service’, and the acronym it spawns, are somewhat amorphous, all-encompassing terms which can be applied to any company offering subscription services to improve their client’s handling of data.
Usually, this will involve migrating data functions from in-house to cloud architecture, which is owned and operated by the DaaS provider. This extensive cloud infrastructure often represents the hand that DaaS organizations hold over their clients, many of whom will lack the resources to operate such extensive architecture themselves.
So, a company specializing in DaaS may provide many functions to their clients. Some focus on storage, using the cloud to maintain vast quantities of data which would be difficult or impossible to maintain via traditional methods.
On the other hand, the organization might provide analytical tools to their clients, often in a similar way to the Software as a Service – SaaS – business model, in which the client utilizes software within their own systems and uses this to gain insight.
Another way in which a DaaS provider might try to enhance a company’s data practices is by offering a consultation service; expert advice which a client can then apply to their business, or powerful reports which can then be used to augment understanding. However, one of the most common ways in which a DaaS provider operates is in direct provision of data; the use of data capture methods and stores to acquire this highly sought after digital resource, and then delivering it to the user. In this sense, the DaaS provider becomes the gatekeeper, mining the data and then licensing it out to buyers.
DaaS: The Case Against
Harnessing the power of a third party organization within your data strategies represents something of a conundrum. Of course, you want to be able to create the best data visualizations possible, and for this you need the best data. Experience tells us that store-bought products tend to be of a higher quality than something we’ve knocked together in the garage, so we go with this option, and we pay a fee to receive top-quality data.
But is this effective? After all, we are authorities in our own industries, we understand the nuances and idiosyncrasies of the markets we operate in, so who could be better positioned to provide this data than ourselves?
Often, the problem is a lack of confidence in the data we have at our disposal. There is also the idea of deference; we assume that ‘the expert’ providing the DaaS service can do it better than we can, so we are willing to pay. However, this need not be the case.
We have the data already. We have more data than we could ever deploy effectively. We have more data then we know what to do with. Every interaction with a client, every new product launched into the market, every move a business makes; all of these things produce data. If we can learn to wield this data – if we can put the systems in place to harness it and apply it to our own organizations – then we have no need for Data as a Service.
DaaS: The Case For
But, as we have seen, DaaS does not simply provide our organizations with data; it gives us the chance to become truly data-driven and to turn our companies into the data-centric businesses we have always aspired to be.
After all, even if we have the data – even if we have data flowing through every process of our business – turning that raw material into a visualization, or using it to gain true insight, is not easy. We may not necessarily have the spare resources to devote to this sort of endeavour, or we may not have the right software in place to corral the data and wrestle it into submission.
So, what do we do? Just like anything in business; when presented with a problem we search for a solution. In many cases, this solution could be provided by a DaaS organization.
It is also important to remember the other benefits a DaaS product can provide. Even if we don’t feel comfortable paying for data which we already have in abundance, we can still derive value from this service. Mentoring and consultation is always valuable, particularly in the early days of a data-driven procedure, and having the cloud architecture in place to securely store data is always going to be positive. It all comes down to what our organizations need, and how we can ensure that we have access to the right solutions.
By adopting a considered approach to Data as a Service, we can make sure that we achieve a demonstrable advantage from it. To do this, we simply need to understand our needs.
Take a look at some of your past data visualizations; what would you like to improve? Were your objectives accomplished? Were there any areas in which your data processes – acquisition, handling, storage, deployment, for example – were found to be lacking?
Answering questions like these, and taking a forensic look at the manner in which you use data, will help you to strategize for what comes next. From here, you will be able to work out precisely what you require, and will have a better understanding of which service providers can help you to achieve this.
Treating DaaS as an amorphous mass is unhelpful. Instead, view each DaaS organization as a solution-provider, and cherry-pick the data solutions that best suit your business.
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