Every business aims to be data driven, but not all of them succeed in that effort. In order to be able to truly derive insights from the data that an organization collects, there are certain foundational capabilities that they need to have capacity for. In order to help more businesses build those foundations, Tarush Aggarwal created 5xData, offering collaborative workshops to assist in setting up the technical and organizational systems that are necessary to succeed. In this episode he shares his thoughts on the core elements that are necessary for every business to be data driven, how he is helping companies incorporate those capabilities into their structure, and the ongoing support that he is providing through a network of mastermind groups. This is a great conversation about the initial steps that every group should be thinking of as they start down the road to making data informed decisions.
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Datafold gives you visibility and confidence in the quality of your analytical data with fast dataset diffing, profiling, column-level lineage, and intelligent anomaly detection. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI, so in a few minutes you can get from 0 to automated testing of your analytical code. Go to dataengineeringpodcast.com/datafold to start a 30-day trial of Datafold. Once you sign up and create an alert in Datafold for your company data, they will send you a cool water flask.
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
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- Your host is Tobias Macey and today I’m interviewing Tarush Aggarwal about his mission at 5xData to teach companies how to build solid foundations for their data capabilities
- How did you get involved in the area of data management?
- Can you start by giving an overview of what you are building at 5xData and the story behind it?
- impact of industry on challenges in becoming data driven
- profile of companies that you are trying to work with
- common mistakes when designing data platform
- misconceptions that the business has around how to invest in data
- challenges in attracting/interviewing/hiring data talent
- What are the core components that you have standardized on for building the foundational layers of the data platform?
- providing context and training to business users in order to allow them to self-serve the answers to their questions
- tooling/interfaces needed to allow them to ask and investigate questions
- most high impact areas for data engineers to focus on in the initial stages of implementing the data platform
- how to identify and prioritize areas of effort
- useful structure of data team at different stages of maturity
- What are the most interesting, unexpected, or challenging lessons that you have learned while building out the business and team of 5xData?
- What do you have planned for the future of the business?
- What are the industry trends or specific technologies that you are keeping a close watch on?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
- Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used.
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