Databricks FinTech Unicorn Presentation

[Audio] Hello, My Name is Max Kruszeski, and for my Fintech Unicorn report I will be covering Databricks.

[Audio] This section will cover the History and Background of Databricks..

[Audio] Databricks is a data-and- AI focused company that interacts with corporate information stored in the public cloud. Databricks was founded in 2013 by a team of professors and graduate students at the University of California Berkely during the AMPLab Project. Ali Ghodsi serves as the CEO, and shares co-founder status with six other professors and grad students, Each member of the team worked on unique projects in the past resulting in the culmination of the final product Databricks. As of February 1st the company was valued at around $ 28 Billion, and is headquartered in San Francisco California.

[Audio] Databricks' 4 core values are: Teamwork makes the dream work, Let the data decide, Be customer and partner obsessed, and Own it. The first value is all about collaboration. Without working together, it is impossible to build a world class organization. Colleagues from customer success, solution architects and account executives have a deep understanding of the challenges their customers are facing and all are willing to help out. Secondly, Data is an essential ingredient to decision-making. Databricks as a product is all about data and as an organization use high-level, anonymized usage data to both get a better understanding of how their customers use the platform and to measure adoption after rolling out new products or features. The third is about relationships, Databricks has a wide range of types of customers and is working together with a significant number of partners. The only way to fully define the right product and turn it into a success is to have a deep understanding of the goals of everyone involved. Finally, "Own it" is about accountability. All employees have a high degree of ownership and that shows in the level of detail in their work. If something needs to happen, Databricks believes you either take care of it or make sure someone else takes on the responsibility..

[Audio] This section will cover what Databricks is, the platform structure it follows and much more..

[Audio] To better understand what Databricks is and its capabilities. We must first get an understanding of data lake houses, the structure the Databricks platform follows..

[Audio] A data lake house is a data management architecture that combines the benefits of a traditional data warehouse and a data lake. It seeks to merge the ease of access and support for enterprise analytics capabilities found in data warehouses with the flexibility and relatively low cost of the data lake. Data lakehouses address four key problems with the traditional two-tier architecture that spans separate data lake and data warehouse tiers, including: Reliability, Data Staleness, weak analytics, and cost. Data lakehouses solves these problems by implementing advanced data processes, Artificial intelligence ( AI) and machine learning support, and SQL tuning..

[Audio] Apache Spark is an open-source, distributed processing system used for big data workloads. Apache Spark is used in the Databricks platform Databricks is a Cloud-based Data Engineering tool that is widely used by companies to process and transform large quantities of data and explore the data. This is used to process and transform extensive amounts of data and explore it through Machine Learning models. It allows organizations to quickly achieve the full potential of combining their data, ETL processes, and Machine Learning. Databricks is the world's first and only lake house platform in the cloud..

[Audio] This section will cover the Market Databricks operates in, as well as future growth opportunities.

[Audio] Because Databricks is the world's first and only lake house platform in the cloud, indicating no direct competitors at this point. Today, more than 5,000 organizations worldwide — including ABN AMRO, Condé Nast, H&M Group, Starbucks, T-Mobile, Regeneron, Shell and many more — rely on Databricks to enable massive-scale data engineering, collaborative data science, full-lifecycle machine learning and business analytics. Being that there are no companies offering a data lake house platform like Databricks at this point, and their ability to raise capital, the future looks incredibly bright for Databricks. The company landed the number two spot on Forbes' 2021 Cloud 100 list, and CEO Ali Ghodsi told Forbes in 2021 that Databricks is IPO-ready. The firm going public would allow for Databricks to continue to grow its platform and its capabilities.

[Audio] In conclusion, Databricks has had a successful journey from when it was founded in 2013, and this success is on path to continue due to their products advanced capabilities, ability to raise capital, and large market share. Because there are no competitors, Databricks will continue to generate revenue through its subscription based SaaS data analytics, AI and cloud based platform until a direct competitor may come along. CEO Ali Ghodsi saying the company is " IPO ready" could also provide more room for the growth if the company does decide to go public..

5. Bibliography. 12. Works Cited “About Databricks.” Databricks , 27 Oct. 2021, https://databricks.com/company/about-us#:~:text=Today%2C%20more%20than%205%2C000%20organizations,machine%20learning%20and%20business%20analytics. Cai, Kenrick. “Databricks Reaches $38 Billion Valuation after New $1.6 Billion Injection.” Forbes , Forbes Magazine, 31 Aug. 2021, https://www.forbes.com/sites/kenrickcai/2021/08/31/databricks-series-h-38-billion/?sh=5a4f5c5a38b3. Databricks, Sherly Angel on, et al. “What Is Databricks: The Best Guide for Beginners 101.” Hevo , 16 Dec. 2021, https://hevodata.com/learn/what-is-databricks/. “Founders.” Databricks , 4 Feb. 2022, https://databricks.com/company/founders. Posey, Brien. “What Is a Data Lakehouse?” SearchDataManagement , TechTarget, 10 Sept. 2021, https://searchdatamanagement.techtarget.com/definition/data-lakehouse#:~:text=A%20data%20lakehouse%20is%20a%20data%20management%20architecture,and%20relatively%20low%20cost%20of%20the%20data%20lake..

[Audio] Thank you for listening! I will answer any questions or comments on the D2L Discussion board..