Data capture and the accessibility of tools to extract value from data are increasing exponentially. These continually improve our ability to optimize, automate and make better decisions.
Most initiatives are only scratching the surface of the value they can extract from data. Data literacy and democratization is essential to not get left behind.
Originally trained as a scientist, I am experienced in working directly with customers to solve challenging analytical problems. This revealed significant opportunity to better use data to optimise, automate and make better decisions.
I have worked in data science developing data-driven solutions and want to contribute back to the community, leading me to create DataMunch.
Examples of solutions I have developed include:
- Health metrics for quantifying scientific instrument health
- Dashboards for monitoring scientific instrument health
- Pipelines for transforming and joining terabytes of data
- Automated reporting tools for semiconductor manufacturing environmental monitoring.
I have created data-driven value through the following philosophies and technologies:
- Building data initiatives and products working from the user backwards
- Leveraging open-source data tools (Python, Jupyter, SQL, dashboarding, ML libraries)
- Leveraging cloud services, specifically AWS: Glue/Spark ETL, Athena, Lambda, Elastic Beanstalk
- Application of models and algorithms to gain insights from data
- Rapid prototyping and iteration using low-code tools.
Outside work, I’m into everything involving mountains including ultra running, climbing, skiing and most backcountry “missions” feasible in the NZ wilderness.
Don’t hesitate contact me through LinkedIn.
-Hamish Lamotte, October 2020