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SAS Enterprise Data Integration Server

SAS Enterprise Data Integration Server

Overview

What is SAS Enterprise Data Integration Server?

The SAS Enterprise Data Integration Server is a suite of products; this legacy edition is now replaced by SAS Data Management Standard.

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Product Details

What is SAS Enterprise Data Integration Server?

SAS Enterprise Data Integration Server Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
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Comparisons

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Reviews and Ratings

(18)

Attribute Ratings

Reviews

(1-3 of 3)
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Filippo Orlando | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Incentivized
The product is used by our company to meet specific needs in the analytics field, for our CRM. In our case, it's used to manage customer segmentation logics and CRM targeting. I think it is the ideal solution, but may not find it's place in other areas or projects.
  • Integrability with different data sources. The provision of native connectors is complete and there is the possibility of implementing new ones.
  • Flexibility in power sources, thanks to the connectors with the main DB and the integration of all types of formats (XML, CSV, JSON, etc.)
  • End-to-end process with the SAS suite. Products such as SAS Visual Analytics allows the visualization of the data produced, or Visual Data Mining and Machine Learning which allows you to perform advanced analysis.
  • It is a versatile product but sometimes difficult to use due to the very close link with the proprietary programming language where specific knowledge is required.
  • Compared to competitors on the market that offer the same functions for the integration perimeter, it is certainly very expensive.
  • It is very simple to use when combined with products from the SAS suite, less so it is being used stand-alone or integrated with other well-known brands.
I believe that in the field of Data Integration, the SAS product is very suitable if the company uses SAS products for all the steps of the data. It is less suitable if used as a stand-alone tool. In our case, to manage customer segmentation logics and CRM targeting, it is the ideal solution.
Data Source Connection (2)
80%
8.0
Connect to traditional data sources
80%
8.0
Connecto to Big Data and NoSQL
80%
8.0
Data Transformations (2)
60%
6.0
Simple transformations
50%
5.0
Complex transformations
70%
7.0
Data Modeling (5)
62%
6.2
Data model creation
50%
5.0
Metadata management
70%
7.0
Business rules and workflow
60%
6.0
Collaboration
70%
7.0
Testing and debugging
60%
6.0
Data Governance (2)
75%
7.5
Integration with data quality tools
70%
7.0
Integration with MDM tools
80%
8.0
  • Implementation time to be expected due to the expertise on SAS tools and its language.
  • Complete and very powerful tool, especially combined with other SAS products.
  • Modern product always in step with the times and needs, certainly not cheap.
The product is best when combined with the other products of the SAS suite. In particular, it's great for the preparation, analysis and display of the data if it is carried out with the products indicated above. When it is combined with products other than those of the SAS suite, the integration and solution of the issues are complex.
It is a good product, but not the best in its field. Very functional if combined and confined to the SAS world. Unnecessarily complex and expensive if outside this scope. I believe that on the market, in relation to quality/price, there are more versatile products that allow greater integration even if less powerful and performing.
The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
This is used department-wide for different clients. There are very limited people who are using it because for handling this tool some experience is required. We use it to make data lakes for fetching data and using it for analyzing patterns.
  • It can process multiple data sources together.
  • It works very fast and is highly scalable.
  • It hangs a lot, that means that while loading huge data it sometimes slows down.
  • No modelling options available in the tool.
It is suited for taking data from multiple sources simultaneously like for example the streaming data of transactions in retail stores. It processes the data at a pretty high pace and gives high results every time.

It is less appropriate sometimes because it hangs sometimes and does not have a large user community available over the internet.
Data Source Connection (2)
85%
8.5
Connect to traditional data sources
90%
9.0
Connecto to Big Data and NoSQL
80%
8.0
Data Transformations (2)
90%
9.0
Simple transformations
100%
10.0
Complex transformations
80%
8.0
Data Modeling (5)
74%
7.4
Data model creation
60%
6.0
Metadata management
80%
8.0
Business rules and workflow
70%
7.0
Collaboration
70%
7.0
Testing and debugging
90%
9.0
Data Governance (2)
75%
7.5
Integration with data quality tools
80%
8.0
Integration with MDM tools
70%
7.0
  • It made life easy as many options are drag and drop. So work happens fast and ROI improved.
  • We can use multiple data sources simultaneously for creation of the data. I think this also increases the ROI.
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
Overall I am satisfied with this product as it meets my all requirements and made my life easy for analyzing the data and especially the streaming data.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
SAS has been used by many users in our organization, mainly business and retail users for running various modeling using SAS optimizer. It allows the user a wider range of capabilities to cleanse and manipulate the data.
  • Manipulation of data
  • Interact directly with visualizations that refine analyses
  • Wide range of delivery reports
  • Licenses are very costly
  • Its not easy to move SAS users to other open source products because of the easy programming in SAS.
SAS Enterprise Data Integration allows the user a wider range of capabilities to cleanse and manipulate the data. Not only can the data be pulled directly into SAS, but before it is finalized it can be transposed, graphed, or altered. Depending upon the number of use cases and business requirements, think before investing.
Data Source Connection (2)
100%
10.0
Connect to traditional data sources
100%
10.0
Connecto to Big Data and NoSQL
100%
10.0
Data Transformations (2)
100%
10.0
Simple transformations
100%
10.0
Complex transformations
100%
10.0
Data Modeling (5)
92%
9.2
Data model creation
100%
10.0
Metadata management
90%
9.0
Business rules and workflow
90%
9.0
Collaboration
100%
10.0
Testing and debugging
80%
8.0
Data Governance (1)
90%
9.0
Integration with data quality tools
90%
9.0
  • We looked at how this tool could not only help us now but what it can do to expand our business intelligence in the future.SAS is great because they have so many different modules and products that a company can simply add capabilities as they grow their internal business intelligence division.
SAS integration is not easy because there are various PAM related modules which require additional vendor involvement. Overall once all integrations are set up, it's a great tool and provides multiple options to users for running their model.
It worked as expected.
Overall SAS is a great product and it's been in the market for decades.
170
Retail, Business, Finance users
3
SAS Administration is a must along with Unix experience.
  • Data modelling
  • Data governance
  • Data optimizer
  • Evaluate other alternatives to avoid license cost
Its overall support, product and cost
Its overall cost, support and product
They have funded the SAS upgrade project last year.
  • SAS programming
  • API calls
  • Integration with warehouse and big data
  • Encryption
  • Data governance
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