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Open source logic programming language compiles to SQL and runs on Google BigQuery, with experimental support for PostgreSQL and SQLite.
Ahana Cloud for Presto turns a data lake on Amazon S3 into what is effectively a data warehouse, without moving any data. SQL queries run quickly even when joining multiple heterogeneous data sources.
Finding success with data analytics requires good tools, good data management, and good strategy. Turn to these best practices to turn your growing volumes of data into better business decision-making.
As your data evolves, you need a way to track the who, what, when, why, and how of those changes. You need a data lineage system.
See how to use the blastula package to send emails with text, graphs, and analysis right from R.
Data rarely comes in usable form. Data wrangling and exploratory data analysis are the difference between a good data science model and garbage in, garbage out.
The past 12 months have revealed how valuable data science can be while also exposing its limitations. Expect big advances in the year to come.
BlazingSQL builds on RAPIDS to distribute SQL query execution across GPU clusters, delivering the ETL for an all-GPU data science workflow.
With so many NLP resources in Python, how to choose? Discover the best Python libraries for analyzing text and how to use them.
We need one platform to ‘process, store, secure, and analyze data in real-time, across all the relevant data sets,’ says MongoDB’s CTO. But not a data warehouse and not a data lake.