The Data Standard
In this episode of The Data Standard, Benjamin Rogojan talks about the importance of Consultant data engineering and the steps engineers have to take to cope with huge amounts of data.
He talks about the problems engineers encounter when trying to analyze different types of data. His passion for finding solutions led him to become a consultant and teach other experts on how to approach specific data analytics jobs.
The process usually requires extracting data from multiple applications and pulling them into a single excel file. Since the data is gathered from multiple sources, there is a lot of room for error. Then he goes on to talk about the need to centralize data inquiries. The idea is to mix all the data into one platform and work with it from there.
The use of data warehouses thats so popular among companies these days is inefficient as analytics takes too long. Many businesses make new changes before they get results from previous implementations. Benjamin explains how speeding up data analytics through a central pile provides much more accurate results much faster.
Many companies use AI to extract data, but Benjamin explains that they are doing it wrong. They use expensive features before they set clear goals, effectively losing money in the process.
Meet The Host
Co-Founder & Board Member of HiQ Labs
Darren Kaplan is 2x Founder and recognized as one of the Top 20 Data Science Influencers in 2020. Darren is the co-creator of The Data Standard, the premier networking user-community for data-science, data engineers, and cybersecurity enthusiasts.
Meet The Guest
Data engineer and data scientist at The Seattle Data Guy
Benjamin Rogojan is a data scientist and engineer with extensive experience designing ETL pipelines, databases, and websites. He worked for multiple startups as well as solutions for existing corporations.