4.1 out of 5 (21 Ratings)

19 Verified Reviews

Microsoft SQL Server 2000/2005/2008/2012/2014

SQL Server Implementation Lengthly but Justified by End Results

MS provided many on-line tools and resources to help with the installation of SQL Server. MS was also made experts available to help us when we became stuck during implementation.

Microsoft SQL Server 2000/2005/2008/2012/2014

MS SQL Server provides solid foundation with capability growth

We have a large base of product knowledge and the integration with Excel is essential. We are also looking at a future expanding our capabilities and delivery with Power BI.

Microsoft Azure Machine Learning

Very flexible and powerful, but has some bugs.

The interface allows for rapid development. There have been some bugs that caused roadblocks.

Microsoft Azure Machine Learning

Azure ML Run Slow

Azure ML is a bit slow. Training on 50,000 data set toom 15 minutes. The data set was housed in the Azure Blob. We also rean into SWAGGER error, which we needed to reach out to Microsoft vender to help trouble shoot.

Microsoft Azure Machine Learning

Implementation was easy but security needs to be thought ahead

The overall experience was good. Having a strategic relationship with MS enables us to have access to resources that typically would not be available to all other organizations. With that the ability to ask the right questions and have Design Sessions enabled us to understand the capability and have a better understanding of how the capability was going to be leveraged.

Microsoft SQL Server 2000/2005/2008/2012/2014

Microsoft SQL Server BI Stack

All worked very well. Minor and few things did not work very well but they were very managable.

Microsoft SQL Server 2000/2005/2008/2012/2014, Other...

Analysis Services

For Analysis Services the research support is relatively limited

Microsoft Azure Machine Learning

Powerful, easy to use, integration with key open source data science tools

Great web-based UI for ETL, modeling, and deployment to web service. Some challenges remain around versions of open source packages supported, but overall the platform is best in class.

Microsoft Azure Machine Learning

Easy to use and to scale, with less than 60% of time and money

We moved the 90% of all our internal machine learning systems to the Azure ML Studio in less than 3 weeks. Now all the process is in strreaming in Azure and we have the possibility to lunch multiply instance of test / learning with less than 60% of the previous time and resources. Using Python and Jupiter notebook integration!

Microsoft Azure Machine Learning

Was easy nedd to mature some aspects

Ease to implement the dificult piece was changing clien culture totake decisions based om information