Monthly Data News (3 Part Series)
Each month, I'll be showcasing some of the great posts, projects and news on all things data from around the internet. Some may be "new news", some may be new to me. In any case, grab a coffee or a tea and have a read of these Data Science and Data Engineering stories.
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With the help of AWS services, the team are building machine-learning and deep-learning tools to automatically tag this content with descriptive metadata to make the archiving process more efficient.
Teasing out insights from one of the most prominent animated television shows of the past three decades.
Amazon Athena adds support for running SQL queries across relational, non-relational, object, and custom data sources
With federated querying, customers can submit a single SQL query that scans data from multiple sources running on-premises or hosted in the cloud.
The majority of organisations now recognise the importance of data as a driver of commercial strategy.
If you really want to succeed as a Data Scientist you need theses soft skills.
You don’t want to be stuck with all this manual reporting so how do you solve this problem?
For data professionals it is the best of times, it is the worst of times.
Visualizing Seattle pet density by combining several shape files and data sources, using Geopandas, Shapely, Pyplot, and Folium.
File formats can be confusing, so lets delve into Columnar file formats (like Parquet) and explain why they're different to regular formats (like CSV, JSON, or Avro)
Airflow is an awesome tool and I love it. But, I initially used it the wrong way, and probably others also do.
That wraps up the news for this month, if you would prefer to receive this monthly update as an email you can sign up here.
Photo by: Matthew Henry