The Rise of All-In-One Data Platforms

The era of investing huge amounts in tools and talent to build modular data stacks is now firmly over with the rise of complete all-in-one data platforms

The average company currently uses over 110 different software tools to effectively run their business. All of these tools tend to be spread out over different departments, and require specialized teams to operate them properly. Given the potential of the data these tools generate to help make better business decisions or improve operational processes, it’s not surprising that companies will at some point need to connect these dots by investing heavily in extra tools to manage this data as well as new data engineers & analysts to manage it.

Unfortunately, not all companies have this ability to make huge investments in both technology and talent to bridge these data silos and build a cohesive data-growth strategy. That’s why the emergence of all-in-one, or complete, data platforms represents a significant paradigm shift. Now the act of collecting, visualizing and acting on data can be done from a single portal. This means now everyone has the chance to get real business value from their data.

Custom and modular solutions: It’s always been done this way

Until now, companies typically followed two distinct paths when it came to getting value from their data. Companies operating on a sufficiently large scale to be generating vast amounts of complex data would build their own custom solutions to meet their very specific needs. Others would instead build up a modular data stack of multiple tools to cover their bases. Both of these approaches though suffer from the same problems.

Firstly, they both require a significant financial outlay. Building a custom solution or acquiring licenses for multiple tools necessitates an investment that can easily run-up a six figure bill. All of these tools then require a secondary investment in hiring extra data analysts and engineers to guarantee a return on that initial investment, who then become the internal (and non-commercially minded) gatekeepers of unlocking the power of this data.

Secondly, to have an effective strategy around gathering, visualizing and acting on data, you need to be able to tie it into a clear business goal. When you go through a process of bringing in expensive new tools and talent, you are highly likely to become handcuffed to the original business objectives that informed the transformation. No matter how well thought out this strategy might be, this reduction in agility and the ability to respond to market pressures is sure to have a consequence at some point during the company’s growth.

So why do companies risk multi-million euro invoices, bloated workforces and a reduction in their operational agility? This simple answer is that it’s always been done this way. The benefits of unlocking customer data far outweigh the costs, so for as long as modular and custom data stack approaches deliver returns, the high prices have been tolerated. With new technologies coming to market though, it is possible to switch to a methodology that requires less commitment in terms of time, costs and resources, while also maintaining much needed agility.

All-in-one platforms: The new landscape of data operations

All-in-one platforms represent a much needed sea change in this discipline as they don’t require any extra data engineering resources to manage them, are low-cost and intuitive to use. They can handle the work of an entire data stack on their own, so they can easily connect to all your existing data sources, ingest & store the data, and then transform, analyze and activate it. You get a single view of your data in a way that helps make the best business decisions without having to undergo an entire organizational restructure.

As intuitive tools designed to be used by business users, they also remove the need of hiring an additional data science team to manage the processes. This in turn helps guarantee business agility as it’s cross-functional through multiple teams allowing anyone to easily execute operations depending on what they need at that particular moment. This accessibility and cross-functionality significantly reduce the cost of investing in this transformation while delivering a higher ROI.

Leveling the playing field and making big data accessible to every business

Collecting & unlocking customer data and the wider growth objectives of companies are intricately linked in the digital economy. This data helps drive business results by enabling better decision making and improving operational processes, so it continues to be essential to have a holistic overview of all this information. Naturally, companies who operate with highly specific and fixed business goals will continue to see a benefit in designing their own modular or custom stacks to cater to this. For most companies though, all-in-one data platforms represent the easiest and most cost-effective way to get more value from their data. This shift in the future of data operations enables companies of all sizes to leverage their data and accelerate their growth.

About the Author

Jonas Thordal, co-founder and CEO of Weld.