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Analytics professionals would agree that our ability to collect data is already much greater than our ability to analyze it. And it’s only going to get worse.
451 Research recently compared the total volume of data organizations manage now with their expectations in two years. Most organizations (43%) reported that they have between 1TB and 999TB of data today, another 34% have over 1PB. In two years, they predict an increase of 28.6% in their volume of data, with the median at 821TB of data under management. Similarly, they expect the mean volume of data to grow at a 28.3% rate, to reach 156PB. Overall, 30% of the surveyed companies expect to handle between 1PB and 499PB of data and 11.4% of them expected more than 500PB. Yet, only about 1% of that data is likely to be analyzed.
For marketers, “analytics don’t answer all the questions they have and the analysis can’t be done fast enough,” notes Gartner. The same is often true in other data-driven functions, including sales, operations, finance and so on.
Another recent study found that 30% of companies brought in new teams to handle new marketing technology. “They weren’t just changing the cars, they were changing the drivers,” remarks Scott Brinker, of chiefmartec.com and HubSpot.
Too much data, too few people to analyze it, and too many organizations willing to keep buying more fast-changing technology. Clearly, this is not the desired outcome of digital transformation nor is it a sustainable business practice. And, as the 451 Research survey predicts, the deluge of data is not likely to stop.
Two solutions can help break the cycle: 1) invest in training your current team, and 2) design an analytics tech stack that can grow along with your data needs. This way, you don’t have to keep switching apps and retraining or hiring new staff to run your tech stack.
Organizations often struggle with workforce training and culture change initiatives (the “soft” stuff is the hardest to do, isn’t it?). But, every organization can use guidelines ensuring that their tech stack carries them through today and few years beyond. This is exactly what our organization did when it decided to invest in data and analytics technology years ago. Seeing how many other businesses struggle with the same process today, we wanted to share what made us successful in building a lasting analytics tech stack and data processes.
In the “Five Technology Tenets of Data-Driven Organizations” white paper, we discuss some of the main principles that helped us build a data automation platform capable of keeping up with the exponential growth in data volume and analytics needs in our organization.
If you’re wondering how to evaluate data tools or dealing with the limitations of your current stack, download our report. It even comes with a handy checklist at the end to use in your evaluation process!