Last year, we recruited $3 million, got featured on TechCrunch, found new customers, hired more employees, attended conferences around the globe, spent thousands of hours on R&D, and invested a lot more effort on sales and marketing. Not everything was perfect, though. Now that 2014 is over and we have gained some perspective, here are six lessons that we learned as a Big Data startup.

1. Users Want Applications, Not Technologies

Our product used to be called “Hadoop-as-a-Service.” We realized that even though Hadoop is a unique framework that’s been in the spotlight over the last few years, what the market really wants to know is what they can do with it. Therefore, we abstracted our technology so that our users shouldn’t have to know that we run Hadoop under the hood, and we focused our efforts on their use cases.

2. The Cloud is Huge

Some estimate that the cloud business is already worth $16 billion and will increase to $93.5 billion by 2019. There’s a lot of potential there, and we felt the growth in our bones.

3. Not Everyone is on Cloud Nine

Despite the cloud hype, organizations still keep a great deal of their data on-premise. We predict that this will slowly change, though it will require a lot of education. In the meantime, we learned to cater to these needs by allowing users to read/write data from/to on-premise data sources.

4. There is a Jungle of Clouds Beyond Amazon

Amazon Web Services are great. Nonetheless, other cloud platforms also have a lot to offer. That's why we added Google Cloud support last year, and we plan to expand support to even more platforms.

5. The Skill Gap is Real

Running a Big Data startup is tough. We face the same challenges as other companies who use Big Data technologies, especially finding skilled professionals. Last year, we jumped over this hurdle via constant self-training, hiring expert consultants, and recruiting top talent. Furthermore, we discovered that a lot of companies just don’t know what to do with their data. They weren’t only looking for tools—they also wanted brain power, as they wanted the brilliant data scientist who will turn raw data into business intelligence. In their absence, we held many consultation sessions with our clients and helped them to become data-driven organizations.

6. More Money, More Power

When we started Xplenty back in 2012, we tried to do it with a very low budget and to slowly grow from there. But raising $3 million last year really boosted our efforts. We expanded into the US market, and we can now deliver easy Big Data processing to more organizations than ever before.