SAS Scoring Accelerator

Eliminate inconsistencies caused by excessive data movement and latency from conventional processes for scoring data. Prevent delays resulting from slow analytical processing. And capture timely insights from big data.

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8.0/10 (Expert Score) ★★★★★
Product is rated as #83 in category Other Analytics Software
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Eliminate inconsistencies caused by excessive data movement and latency from conventional processes for scoring data. Prevent delays resulting from slow analytical processing. And capture timely insights from big data.

SAS Scoring Accelerator
SAS Scoring Accelerator

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Customer Reviews

SAS Scoring Accelerator Reviews

Ritesh N.

Advanced user of SAS Scoring Accelerator
★★★★★
SAS Scoring Accelerator - a win for all

What do you like best?

SAS Scoring Accelerator is an enabler component from SAS that helps users to translate scoring models developed in SAS EMiner and SAS/STAT into database-specific functions, and thus helps execute them directly within the database environment. This saves the I/O and time of data transfer making execution really fast. It also automates model-scoring processes within so users can improve model scoring performance and achieve faster time to results.

What do you dislike?

Instead of projecting it as a dislike, I would like to project it as extra effort. Users should know the best practices of of database. The better the user is with the data base, the easier it is for them is to understand and use SAS Scoring Accelerator Product. This helps get more out of the product.

Recommendations to others considering the product:

I would really recommend the product to SAS fraternity especially who are in Banking and doing modelling stuff. It is a wonderful product, as it really speeds up the execution and thus enables quicker time to deliver the results.

What problems are you solving with the product? What benefits have you realized?

In simple words, it has below advantages:

1. It reduces excessive data movement from Data base to SAS Environment and vice versa.

2. It streamlines analytic deployment processes, giving a uniform and accelerated approach across the model

3. Enhances the productivity of analytic and IT groups, because it helps timely insights to decision makers by efficient utilization of resources in data warehouse platforms, analytic software. Thus it results in better, reliable and consistent delivery.

4. Enables IT to more efficiently use their resources and reduce costs, because it is less resource (CPU, Network, I/O) hogging. Thus enable optimum utilization of IT resource.

Review source: G2.com

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