Benefit from an architecture for big data science that allows you to perform advanced analytical tasks on large volumes of data in an interactive fashion – right in the database. Using R, Java, Python, Lua – or any analytic programming language you prefer. Run analytic functions and UDFs that fully leverage the database’s features, such as massively parallel processing (MPP), columnar storage, compression, and in-memory so that they run faster than ever before.
Download our free Business White Paper to gain a more thorough understanding about a new systems architecture:
Revolutionizing Data Science and Advanced Analytics
- You know the ability to provide sophisticated advanced analytics and incorporate a variety of available data sources is crucial to your success.
- You’re finding it nearly impossible to combine advanced data science and classical relational analytics in your organizations.
- Exasol will support you by bringing R, Python & co directly to the place where the large data volumes are stored.
The Exasol solution
- Exasol offers a new system architecture that will allow your team to perform advanced analytical tasks on large data volumes in an interactive fashion – directly in the database using any Data Science programming language (R, Python, Java, Lua, and much more).
- We provide parallel script execution across a cluster of standard servers that makes data science on big data easily available and affordable.
- We have created open-sourced packages to integrate the EXASOL database directly into your R or Python environment.
- You will be able to unite different islands in your company by using Exasol for all your analytic tasks, both standard and advanced analytics.
- Solve complex analytic challenges like predictive analytics with ease by bringing Artificial Intelligence (AI) and Machine Learning (ML) algorithms directly to the data.
- Save money for more expensive analytic tools.
- Exasol delivers a 360-degree view of your business. Our clients are able to predict future trends and needs with precision, giving them an undeniable edge.
- Teams are able to make data science concepts available to their BI users with transparency.
For us to continually provide reliable analyses, a database with high scalability is imperative.Jan Karstens, CTO, Blue Yonder