The Internet of Things (IoT) has ushered in a new era of technological advancement, connecting devices and enabling
90% of start-ups struggle to handle ever-increasing data infrastructure costs. Do you think that your start-up’s current data infrastructure is cost-effective?
No matter if your product deals directly with information or not, data pipelines for ingesting and manipulating data are something that every startup needs. The needs may vary with complexity and capacity, but the fact of the matter is – data needs are everywhere, ever-growing and it all boils down to is your data infrastructure truly cost-effective?
Developing a data infrastructure in-house may initially save your start-up money – but these temporary, unscalable solutions end up requiring higher investments and consuming more manpower than expected. Meeting software capacities while enjoying reduced expenses is something every start-up hopes for, but this ideology has been proven to come up short.
So how does a start-up afford to implement a state-of-the-art data solution from the get-go?
It begins with a solution that takes into consideration cost, flexibility, and capacity.
Data Infrastructures – Data Can and Will Cost You.
The costs associated with well-established data IT infrastructures for startups with the capacity and flexibility to adapt to ever-changing businesses are large and ongoing. Whether implementation, maintenance, or scaling, the human power needed and the expenses associated with adapting data infrastructures, can make anyone cringe. Even if building in-house may seem like a feasible option, once you consider the costs and labor needed to make changes the question arises, is this really effective use of my software engineering talent?
Tackling the Data Issue in Four Simple Steps
As the data industry has grown, any player affected by or privy to information in regards to this ever-changing domain has attempted to find a solution to their data needs. But, how exactly do you solve one of the largest cost issues of this decade?
1) The Build or Buy Equation: A Short and Long Term Consideration for Start-Ups
Flexibility does not necessarily mean doing it yourself, it means balancing between short-term flexibility and long-term bondage. Built solutions tend to be the most flexible, creating the best optimization of time and accuracy for your specific needs. However, the more specific and unique the solution is, the higher the long-term costs are. The burden of keeping what served you well in the early days of your data infrastructure for your start-up becomes unbearable when you need to adapt, scale, or when changes need to occur. The answer to this conundrum is choosing a platform that was designed for developers and gives the benefits of a well-built and continually developed platform as the foundation on which you can implement your specific needs – offering rigidity on the lower levels with full flexibility on an application level.
2) Cloud Computing and Cloud Data are not the same
Cloud computing changed the world of IT as it took the overhead of server rooms and IT personnel, trading it in for unlimited availability and total flexibility. Data pipelines as a (cloud) service tend to result in increased overhead as these entirely data-based services charge you for data handling costs. The result is rather than saving costs – as you test and grow, data is consumed more quickly leading to scary, recurring monthly bills that seem to just keep rising. The solution is enjoying the benefits of cloud computing but keeping data to yourself with a platform that provides maximum flexibility with minimal limitations – allowing your data team to create and expand as needed, without worrying about the associated bandwidth costs of doing so.
3) Full Reign of Your Data Infrastructure with a 360° View
Cost reduction is not enough. Full transparency and cost predictability are vital in a continuously growing and changing start-up data infrastructure. Why? Because an easily observable process sheds light on issues or events that are not in sync – the culprits responsible for jacking up your next data bill. Having full reign over your data process allows for easier, faster honing in on complications and fixing them. Controlling expenses within a start-up is difficult to imagine and even more difficult to put into action, with predictability comes power, and a fixed, known price, is the ultimate strength. With a platform that reveals how each cog in the machine is running, your business can enjoy cost savings at every stage from implementation, to maintenance and even as you scale.
4) Do More For Your Data, With Less
The compute effectiveness of your data flow is another vital aspect of an efficient data infrastructure for a start-up. The ability to do more with the same resources is the definition of cost-effectiveness and is no longer a pipe-dream. Now you can guarantee your pipelines receive only the resources they need when needed.
“Time and money are your scarcest resources. You want to make sure you’re allocating them in the highest-impact areas. Data reveals impact, and with data, you can bring more science to your decisions.”Matt Trifiro, Vapor IO
With a platform that allows you to fully manage your data stack, efforts and resources that would have gone towards mere maintenance are minimized – leaving time for what matters most – transforming data into usable business insights.
Datorios: Tailored For Your Start-Up Business
At Datorios, we understand the constraints of growing companies and as one ourselves, the state of mind as we move forward. This is why the principles on which Datorios was built can serve any growing operation, at any stage, as the one platform for evolving data pipeline needs.
By streamlining processes, providing full transparency, offering cost predictability, and allowing you to fully manage your data stack, the Datorios platform is tailored for the needs of start-up culture and the ever-so-common move fast mindset. With a set-pricing model, Datorios’s platform will save time and money for any start-up’s data infrastructure, now and as it matures, today, and in the years to come.
Enjoyed Part 1?
Check out Part 2 which dives into how to implement a sustainable, scalable data infrastructure for your start-up.
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