Article by Patrick Nelson for siliconANGLE The key to successful artificial intelligence-based advanced analytical training is augmenting internal data with external, according to data science
What are Recommender Systems? You’ve seen it everywhere. Every big tech company is now using some kind of Recommender System in their platform. Facebook suggests friends, Netflix recommends movies, same
As published on Medium. Every Data Engineer who uses Elasticsearch as a documents store, knows that there are many parameters that affect the queries latency, throughput,
Have you ever found yourself developing PySpark inside EMR notebooks? Have you ever found yourself debugging PySpark locally, but wanting to run it over a real
Whatever your business challenge, you’ll need data you can rely on to solve it. It’s highly unlikely that the data you have in-house offers the scope
Finding the right vendor for alternative data is really hard. Each has their own processes and schema, down to the format the datasets are provided in
Few types of regulation have ever proved to be as far-reaching or game-changing as GDPR. Pretty much any organization in the world with an online presence
In the business of external data enrichment for data science, the main focus is on the ability to provide a fast and scalable way to aggregate, join and
As organizations move from data analytics to data science, their data needs evolve, too. Without data, there is no machine learning (ML). But we’re not talking
