In-memory analytics and interactive, analytical data preparation, exploration, modeling and deployment deliver precise answers instantly.
Delve deeply into big data for fast, accurate insights.
Proven, state-of-the-art statistical algorithms and machine-learning techniques deliver precise answers quickly. Use multiple analytic approaches to explore big data. And unearth insights for making high-impact decisions.
Give your data scientists a productivity boost.
A fast, in-memory analytical programming language allows multiple users to analyze big data simultaneously and interactively. Data scientists can prepare, manipulate, transform, explore, model, access and score data – from a single environment.
Take advantage of a scalable environment.
Accessing, preparing, modeling and scoring data has typically meant piecing together different programming languages or products. And such piecemeal solutions simply can't scale. But no more. From data preparation and exploration to model building and deployment, our solution is tested and proven – and scales to fit your production environment.
Stop multiple, unnecessary passes through the data.
Our in-memory infrastructure eliminates costly data movement and persists data in memory for the entire analytic session. This significantly reduces data latency and provides rapid analysis at lightning-fast speeds.
Key Features
Interactive programming
Multiple users can analyze large amounts of data concurrently by interactively submitting SAS code through SAS Studio, a web browser interface.
In-memory analytical processing
Fast analytic computations are optimized for a distributed, multithreaded and scalable in-memory environment for high-value, real-time decision making.
In-memory data persistence
Data is held in memory to boost speed and reduce latency.
Analytical data preparation
Includes capabilities for accessing and manipulating data, transforming and creating variables, and performing exploratory analysis.
Model development
Enables fast creation, evaluation and comparison of multiple statistical models.
Statistical algorithms & machine-learning techniques
A huge breadth and depth of analytical techniques can uncover patterns and trends faster than ever before.
Text analytics
A wide range of text analysis techniques lets you analyze unstructured – as well as structured – data.
Recommendation system
Personalized, meaningful recommendations are generated in real time with a high level of customization.
Special Series
Big Data Matters
What’s the point of storing huge volumes of data in Hadoop if it’s a huge hassle to do anything with it? It’s time to rethink your approach. We’ll show you how to tap the enormous potential buried in your Hadoop data stores – faster than your competitors. And without having to move your Hadoop data to analyze it. In this webinar, you will:
- Learn how to bring the power of SAS Analytics to your Hadoop environment.
- See SAS In-Memory Statistics in action.
- View demos on supervised learning and recommendation systems.
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