This year, Keboola is celebrating its 10th anniversary.
This year, Keboola is celebrating its 10th anniversary. Being in the data analytics/business intelligence market for so long, it gives us a unique insight into how the market is changing and what the future of data analytics looks like. In the end, we see that deciding not to build Keboola as a black box for one particular use case was not only a good decision but crucial for our future opportunities.
Right from the start, we’ve been building our software on the premise that the cloud is the future. We also believe that transparency is the key. Both to getting the most from the platform as well as maintaining data security, as opposed to the black-box solutions. As the cloud is standard these days, and companies are now really experiencing the pain of being vendor-locked, we’re really happy that these values holding are strong, more so than ever before.
When Keboola started its journey, the only people talking about data were data analysts and data scientists. On the other hand, businesses leveraging their data needed to invest heavily on IT, but it was very hard just to mine your own data, and the ability to code was the only way to use it properly. Things have changed, and getting data from a single source is now easier than ever. The data analytics/business intelligence market has grown enormously, and nowadays you have a specialist app for almost every use case.
For a long time, we struggled to define the role of Keboola in that process. We did not fit any of the standard product categories - each of them was too narrow for us, and many of them would see us as a competitor to companies that have actually been our partners. So, we’re hopeful about the growth of the new emerging category, described by Gartner, who defined the market as DataHub iPaaS. This category suits us very well, and we’re extremely proud that by being in touch with Gartner it officially recognizes Keboola as a relevant iPaaS Vendor for Gartner customers.
Thanks to more and more data sources, specialist apps, machine learning algorithms and agencies specializing in data science, we can see our role clearly now: being the best platform to retrieve data from sources, working with data in a safe environment, automating it and using it for a particular use case - from managerial reports to the basis of machine learning. Most of the other vendors focus on one use case, but we remain universal - Keboola fits into any stack of data tools that you are using. We unify the technologies and make them accessible to business people.
This is also why we get amazing feedback from our enterprise customers - Keboola doesn’t drain precious IT resources and its also often used to circumvent missing connectors to legacy systems.
By defining our role and looking at the current situation on the market, we feel that our opportunity to grow has never been greater. So, we’ve opened our fifth office - after Prague, London, Singapore and Vancouver. I’m happy to announce that we now have team of 7 in Chicago, USA, myself included, because I’m moving to Chicago with my family in December.
Our mission in the US is simple - to find our #dataheroes. We used the term Data Hero a lot internally, but the context was a person who was responsible for Keboola implementation at an organization. But the more we’ve been using the term, the more we’ve found it really appropriate. Because it doesn’t really matter if the person is a CEO or data analyst. Rather, the main thing we’re looking for is his or her desire to make a change within the company by using data.
If you’re reading this, the chances are that you know Keboola already. So, I’d like to ask you to help us in our effort to help other companies to fight off the “Googles and Amazons of their domain” or to put it another way, to enable thousands of companies to achieve their goals of becoming the new Amazon.
We’re looking for partners. We have a great relationship with GoodData, Snowflake, Looker and consultancy firms such as Deloitte. But above all, we’d like to talk to innovators within the enterprise or rapidly growing companies, so that we can arm them with data.
