Under the Hood: Advantages of using Python with a massively parallel database

Logo
Presented by

Badr Ouali, Vertica Data Scientist and Steve Sarsfield, Director of Product Marketing, Micro Focus

About this talk

Python is a powerful programming language that is a good choice for many types of analytics. It is rapidly becoming the language of choice for scientists and researchers of many types. Now by combining a massively parallel (MPP) database like Vertica with Python, you can overcome many scale and analytics challenges that sometimes challenge Python users. Python users can achieve a simplified path to do as follows: • Analyze more data at greater speeds • Breeze through data preparation with the database’s SQL capabilities • Quickly make the most of advanced database analytics like time-series and geospatial • Benefit from in-database machine learning for predictive analytics • Leverage data as it sits in-place on the cloud or Hadoop without having to move it Join this webinar to understand how to expand and enhance your Python analytics with Vertica. Vertica’s built in integration with Python allows for more data and deeper analytics. As a very efficient database for massive amounts of data, Vertica’s optimizations and advanced analytics can help you achieve new heights as a Python programmer.

Related topics:

More from this channel

Upcoming talks (2)
On-demand talks (161)
Subscribers (36905)
The Vertica Unified Analytics Platform is built to handle the most demanding analytic use cases and is trusted by thousands of leading data-driven enterprises around the world, including Etsy, Bank of America, Uber, and more. Based on a massively scalable architecture with a broad set of analytical functions spanning event and time series, pattern matching, geospatial, and built-in machine learning capability, Vertica enables data analytics teams to easily apply these powerful functions to large and demanding analytical workloads. Vertica unites the major public clouds and on-premises data centers, as needed, and integrates data in cloud object storage and HDFS without forcing any data movement. Available as a SaaS option, or as a customer-managed system, Vertica helps teams combine growing data siloes for a more complete view of available data. Vertica features separation of compute and storage, so teams can spin up storage and compute resources as needed, then spin down afterwards to reduce costs.