Blog Summary: (AI Summaries by Summarizes)
- Companies are seeing efficiency gains and ROI from using Big Data technologies.
- However, the vast majority of teams fail and never get something into production.
- The top 5 reasons why data engineering teams fail at Big Data are discussed in a new talk based on the Data Engineering Teams book.
- Getting mentoring for the team and training on new technologies can prevent these failures.
- Advanced training on Big Data technologies is available.
At Strata London, I premiered a new talk based on my Data Engineering Teams book. Companies are seeing great efficiency gains and ROI from using Big Data technologies. However, the vast majority of teams fail and never get something into production. I want to prevent that failure and here are the top 5 reasons why data engineering teams fail at Big Data and what to do about it.
If your team is just starting out with Big Data, I highly recommend getting some mentoring for the team. This will prevent these failures.
You’ll also want your team to get training on the new technologies. You get that advanced training here:
Companies and conferences: If you would like me to do this talk at your company or conference, please contact me here.
