We all have a friend who’s bragged about getting the greatest deal ever on a used car, right up until they’re calling us from the side of the highway because their new hot rod doesn’t work quite as well as advertised. Some of us, too, have been that unlucky buyer, watching the smoke curl from our engine and wondering where we went wrong. 

Making a decision on a big purchase is tough. Apart from trying to rationally weigh the pros and cons, we’re also influenced by our rapport with a salesperson, or by the shine of a fresh paint job. With all the factors at play, it’s no wonder we’re sometimes stuck with buyer’s remorse. 

For decision-makers at large enterprises, the challenges of evaluating a purchase are amplified. It’s not just the size of the deals that complicate matters. Business owners also must assess cutting-edge technologies, and choose the right ones before their competitors, in order to stay ahead. The process carries risk, to be sure, but also reward. Just ask Netflix, which dominates the streaming media market thanks in part to a 2008 bet that put their entire business on some new thing called the ‘cloud.’

The hot business purchase today, besides TikTok (have you put in your bid yet?), is the streaming data warehouse, a system for analyzing data in real-time. Chief Data Officers, VPs of Analytics, and other business owners are in constant search of capabilities that will help them capitalize on the wealth of data they now generate. However, the traditional data warehouse tends to buckle under the speed and scale of today’s data, and remains expensive and complex to integrate. Like with cars, there’s a lot going on under the hood, and many a buyer has wound up with broken down systems that bring the business—if not their job—to a screeching halt. 

So what should business owners do when they’re stuck on the side of the highway? The answer isn’t to give up on getting where they were going. The trend towards data-driven, real-time decision-making as a crucial capability for any business is not reversing itself anytime soon, especially as our data-powered world becomes increasingly fast-paced and complex. Instead, business owners should look to streaming analytics and machine learning capabilities that were built for the speed and scale demanded today. 

One such solution seeing rapid adoption among major enterprises is the streaming data warehouse, a data analytics platform delivering real-time analysis on incoming data streams. While traditional data warehouses focus on the first mile of ingesting and storing data, the streaming data warehouse can perform simultaneous streaming and analysis, giving organizations results that always reflect the latest data. 

Fast, powerful — sounds kind of like a Ferrari, right? Well, here’s where the car analogies might have to end. Sports cars are notoriously difficult and expensive to maintain, but the streaming data warehouse actually simplifies the analytics process and limits machine learning operational costs. It does so by combining streaming, location, graph, and machine learning capabilities into a single platform, which curbs the need for complex integrations between a patchwork of analytics tools included in an ecosystem for each type of workload. The big red bow on top is that by incorporating all these various analytics pipelines, the streaming data warehouse gains enhanced context from having all of an organization’s data available for analysis, resulting in far more accurate results. 

Sound too good to be true? Take one for a test drive (last car reference, I promise). Kinetica is a streaming data warehouse that offers free use for 30 days. It’s used by organizations trying to incorporate high-velocity streaming data and glean the full business context of all their data, taking into account factors like location, time, and interrelationships. With reliable analysis, long-term scalability, and real-time results, Kinetica is a favorite of business owners who want their organization to be on the cutting-edge — without the buyer’s remorse.

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