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Topic: Building a Robust & Scalable data infrastructure
Speaker: Kelvin Oyanna, Co-Founder & Head Data Analytics at Onesphere
Kelvin Oyanna is a data engineer & Business Intelligence professional with core expertise in building optimal data solutions including: infrastructure, pipelines, tools, etc. to consolidate data in a warehouse and serve useful insight from data.
He spent the past few years helping businesses adopt a data-driven culture, built optimized data infrastructure & data solutions to make sense of their data.
The use of data in businesses becomes increasingly important as its number of users grows. In the early days of any B2B startup, you have to meet with every single customer yourself to get them on-board, so understanding what will get them using the platform becomes a case of simply asking them. However, as business scales, this approach to making decisions no longer works.
It is rare to find part of a data stack that will work well no matter your scale. So as the next best thing we’ve focused on a modular stack.
To ensure that there is no impact on production data or performance, it is essential that a separate database is used for data warehousing. Even then MySQL or PostgreSQL are not ideal options.
This is where columnar databases like Redshift, BigQuery and SnowflakeDB come in. These are sometimes referred to as Analytical databases because their distributed and columnar structure is optimized for that analytical workload. As you collect more data this makes a huge difference to query response time.
Participants will get to learn:
- How to build a scalable database system
- Technologies from production to deployment.
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Организатор: ODSC Kyiv Data Science
ODSC brings together the open-source and data science communities with the goal of helping its members learn, connect and grow.
The focus of this Meetup group is to allow ODSC to work with Meetup groups, non-profits, and other organizations to present informative lectures, workshops, code sprints and networking events to help grow the use of open source languages and tools within the data science and data-centric community. As such, our specific goals are:
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