AiThority Interview with Amnon Drori, CEO at Octopai
Know My Compnay
What is your experience about the interaction with smart technologies like AI and Cloud-based analytics platforms?
While data management needs are growing, it became impossible to continue to do it manually. This means that you need to be able to ‘change the physics’ in order to balance the huge demand for data vs. the inability to deliver due to manual work being done. Automation that leverages ML and AI make it available. 12 years ago, when I was working for a company called Panaya (acquired by Infosys) that was automatically doing ERP upgrades, we saw how automation software is capable of replacing manual work by delivering in 24 hours what 10 people could do manually in 3 months. Octopai is my second company, and I see the power of automation and how it enables organizations to achieve things that they could not if they continued doing things manually.
How did you start in this space? What galvanized you to start Octopai?
I come from a long history utilizing metadata. I was CRO of Cooladata, Senior Director of Sales and Marketing at ModusNovo, Vice President of Zend Technology, and Vice President of Panaya. Over the years, I noticed that Business Intelligence teams suffer from the lack of one comprehensive tool to track, analyze, and synthesize all of their metadata.
Many times I found myself in meetings with CFOs in which everyone at the table had different data about the same numbers, whether it be customer acquisition, burn rates, compliance figures, and more. Which was the correct figure? Who was right and how was everyone else wrong? Without complete, automated data lineage, it took weeks to find the origin of these competing numbers and also correct every other report that was damaged from them. Companies must be able to rapidly identify data lineage, both backward to its source and forwards to their destination reports. Without this ability, company activities can be crippled.
I founded Octopai to empower BI groups to keep track of data at every stage of its movement, saving companies time and money by ensuring consistent, accurate, reliable data.
What is Octopai and how does it transform Metadata Management?
Octopai’s SaaS solution automates metadata management and analysis, enabling enterprise BI groups to quickly, easily and accurately find and understand their data for improved operations, data quality and data governance. Octopai’s sophisticated cloud-based metadata analysis platform includes modules for data discovery, horizontal (system-to-system) and vertical (column-to-column) data lineage, and an automated Business Glossary that can be implemented in less than 24 hours. It is the only metadata management system that offers such complete lineage analysis and automates its setup, saving Business Intelligence teams countless hours of manual data input.
Which industries would benefit from accessing your products and services? Which geographies have been the fastest to adopt metadata BI tools?
Every enterprise would benefit because all enterprises run on data. So far, we’ve worked with companies in insurance, fin-tech, healthcare, transportation, banking, and more. The geographies able to adopt metadata BI tools most quickly have been North America, Western Europe, and Australia.
What are the specific challenges that you solve for your customers?
Any metadata management issue you can think of, we can solve. From compliance issues like GDPR to legacy migration problems to merging data across platforms and ETLs, and we can integrate with any reporting tool, like PowerBI, Tableau, and more.
What is the state of Metadata for BI and Big Data Analytics in 2019? How much has it evolved since the time you first started here?
So much has changed in the last 3 years. When we first got started, we had to do major market education, as few people knew what metadata management meant, let alone metadata management automation. Today, the need for metadata management is clear. We now focus our efforts on educating people on the various use cases for metadata management, and more importantly, the fact that metadata management means different things to different people. Some people need metadata management to help them with their data governance strategy, some to implement a data catalog or business glossary, some for daily BI operations such as reporting errors or business changes, and some for migration projects.
Which platforms and technologies does Octopai support?
The Octopai platform provides one source of truth for all business users, including an automated business glossary, metadata scanning, and visual mapping. It integrates with a wide range of tools, from ETLs like IBM DataStage and Microsoft SQL server to Databases like Oracle and Teradata, to reporting tools like PowerBI, Tableau, and Qlik.
How should young technology professionals train themselves to work better with Metadata automation and AI-based tools?
Young people should become aware of newly available technologies and tools that are built to support the new era of extensively using data that keeps changing all the time. There is a lot of information on the web, but by joining technology companies either as a student, apprentice, or a new employee, you can expose yourself to the available technologies and become up-to-date with what is either being developed or already in use.
What is the biggest challenge to Digital Transformation in 2019? How does Octopai contribute to a successful digital transformation?
Part of becoming digital is the ability to transform your data (e.g. to the cloud). At the same time, you need to be confident that any transformation will not damage the data or skew its value and purpose. This is where automation comes into play. Leveraging automation and technologies like Machine Learning helps make transformations and modernization of data fairly easy and trustworthy. Octopai’s automation platform helps organizations manage their data accurately.
Where do you see AI/Machine Learning and other smart technologies heading beyond 2020?
Time will tell that, but the growing use of Machine Learning and it’s increased sophistication will enable it to make more decisions for the benefit of humankind. I suspect that it will be used across industries (banking, health, transportation, food and more). This will help personalize service for any individual on the planet.
The Crystal Gaze
What Cloud Analytics and SaaS start-ups and labs are you keenly following?
It would be interesting to see what Google, Microsoft, Amazon, and Facebook will do to leverage the huge amount of data they have on their users. On the one side, they enable an analysis of data to enhance the quality of their offerings. At the same time, this data can be misused by others.
What technologies within AI/NLP and Cloud Analytics are you interested in?
As a tech leader, what industries you think would be fastest to adopt Analytics and AI/ML with smooth efficiency? What are the new emerging markets for these technologies?
I suspect that industries like Health, Autonomous Mobility (cars), and Food will leverage ML and AI.
Name one person in the industry whose answers to these questions you would love to read:
Thank you, Amnon! That was fun and hope to see you back on AiThority soon.
Amnon Drori is the Co-Founder and CEO of Octopai and has over 20 years of leadership experience in technology companies. Before co-founding Octopai he led sales efforts at companies like Panaya (Acquired by Infosys), Zend Technologies (Acquired by Rogue Wave Software), ModusNovo and Alvarion, and also served as the Chief Revenue Officer at CoolaData, a big data behavioral analytics platform. Amnon studied Management and Computer Science at the Open University of Tel Aviv.
Octopai was founded in 2015 by BI professionals who realized the need for dynamic solutions in a stagnant market. Octopai’s SaaS solution automates metadata management and analysis, enabling enterprise BI groups to quickly, easily and accurately find and understand their data for improved operations, data quality and data governance. The company was recognized as a Gartner Cool Vendor for Data Science and Machine Learning in 2018 and their investors include North First Ventures, Gefen Capital and iAngels.