Databricks is a successful private data analytics company based in San Francisco. But how did it all start? Believe it or not, Databricks is the result of Ali Ghodsi, along with 6 other Berkley students, taking classes at Berkeley in 2013. Ali, along with Scott Shenker, Ion Stoica, Andy Konwinski, Patrick Wendell, Reynold Xin, and Matei Zaharia They found their inspiration to create Databricks from the lessons learned while at Berkeley. Ali began his career at Databricks as Vice President of Engineering and Product Management. In 2016 he was appointed CEO of Databricks.
1. You think current curricula need more statistics courses
During Informatica World 2019, Ali Ghodsi sat down for an interview with John Furrier and Rebecca Knight. Furrier asked Ghodsi what he would add to today’s college curricula that would enrich the curricula. Ghodsi responded, “What is missing and needed today are statistics… 10-15 years from now, you will need some kind of statistical knowledge. So you need to know what the statistical terms mean. “
2. One billion investors
During a March 10, 2021, interview with Sky News, Ian King asked about the last billion dollars received from investors and how Databricks would use that money. Ghodsi said that much of that money would be used to expand his company internationally, expanding to Asia, Europe and Latin America. He also claimed that a good part of that investment would be spent on research and development. Top sponsors include Salesforce, Microsoft, Amazon, and Google, among others.
3. It all started with a comment from fellow students
Databricks is a successful private data analytics company based in San Francisco. But how did it all start? Well, you could say that it all started at Mid-Sweden University. When Ali began his university life in Sweden, he had a roommate who inadvertently opened his eyes and set him on the path to success. It seemed like this roommate told Ali that the business degree he was seeking would make him Ali’s boss one day. Well, Ali had none of that, and ended up with her own MBA instead!
4. He is considered one of the true founders of AI.
Databrick co-founders like Ali are known as the true founders of AI. In fact, due to their extensive research and development in the field of data analysis, they have become something of a celebrity. People from all over the world are reported to come to Databrick’s San Francisco offices just to get an autograph from Ali! After providing Facebook and Google with exemplary work, Ali realized that these companies possessed vast amounts of data that had to be used to their advantage, which they accomplished.
5. Helped develop Apache Spark
Apache Spark was created and developed at the University of California, Berkeley. An open source project, designed and developed to process data in large batches, but in real time. Real-time data processing means that technology like facial recognition can work properly. The original author was one of the founders of Databricks, Matei Zaharia, with the help of Ghodsi. Spark is extremely versatile and can be used in a variety of businesses, from banking, healthcare to biology.
6. Ali has decided to keep Databricks privacy for now
At the time of writing, Ali has made the decision to keep Databricks private for the time being. Ali’s reasons were sound and logical. Once the business goes public, they must get used to the rules and regulations of each different place. As such, it is as if you are starting another business from scratch. Not only that, but according to Ali, there are quite a few things that a company can strategically do for itself while it is private that it cannot do when it is public.
7. “Equity of dominant resources”
Dominant Resource Fairness (DRF) is a landmark document that introduced a new way of resource allocation. Here, users are encouraged to share resources. This is accomplished by ensuring that no user gets more pieces of the pie than another. In other words, if you have 10 users, each of the 10 users gets 1/10 of the dominant resources. Therefore, it has an equity-based model in regards to the resources used. Indeed, the dominant resource equity concept helps ensure that data is equally available to the public.