Alteryx Analytics vs Amazon SageMaker

Alteryx Analytics

I wish I had found and used Alteryx Analytics years ago. Having multiple data sources with a variety of naming conventions for our businesses we spent WEEKS cleaning/reorganizing/renaming fields in our data to be able to consolidate. We did this on one set of reports for one use. Each time we wanted an update this process would need to be repeated. This took tons of useless admin time. Had we had Alteryx we could have created 1 identifier, noted all the different naming conventions or issues, selected the ones we wanted and created the workflow to use it over and over and over again on any data we wanted. Build once - use multiple times. It would have been (and now is) a HUGE time saver. Plus any new anomalies are identified by the program as errors so you can "autocorrect" them in the same workflow. Alteryx is a miracle in my opinion.

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Susan Knolla

Director People Analytics

J.D. Irving, LimitedPaper & Forest Products, 10,001+ employees

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Amazon SageMaker

Amazon SageMaker is a great tool for developing machine learning models that take more effort than just point-and-click type of analyses. The software works well with the other tools in the Amazon ecosystem, so if you use Amazon Web Services or are thinking about it, SageMaker would be a great addition. SageMaker is great for consumer insights, predictive analytics, and looking for gems of insight in the massive amounts of data we create. SageMaker is less suitable for analysts who do generally "small" data analyses, and "small" data analyses in today's world can be billions of records.

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Thomas Young

Owner, previous CEO

Econometric StudiosFinancial Services, 11-50 employees

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Feature Rating Comparison

Alteryx Analytics

7.9

Amazon SageMaker

—

Pixel Perfect reports

8.0

—

Customizable dashboards

6.7

—

Report Formatting Templates

9.0

—

Alteryx Analytics

8.5

Amazon SageMaker

—

Drill-down analysis

8.3

—

Formatting capabilities

8.2

—

Integration with R or other statistical packages

9.5

—

Report sharing and collaboration

8.0

—

Alteryx Analytics

8.7

Amazon SageMaker

—

Publish to Web

8.2

—

Publish to PDF

8.5

—

Report Versioning

9.0

—

Report Delivery Scheduling

8.9

—

Alteryx Analytics

7.9

Amazon SageMaker

—

Pre-built visualization formats (heatmaps, scatter plots etc.)

8.0

—

Location Analytics / Geographic Visualization

7.5

—

Predictive Analytics

8.3

—

Alteryx Analytics

8.3

Amazon SageMaker

—

Multi-User Support (named login)

8.0

—

Role-Based Security Model

8.0

—

Multiple Access Permission Levels (Create, Read, Delete)

9.0

—

Alteryx Analytics

4.0

Amazon SageMaker

—

Responsive Design for Web Access

4.0

—

Pros

Cleaning datasets
Preparing data for analyzing
Customer data analytics
Transforming data from one format to other

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Sanket Bharaswadkar

Process Analyst

HoneywellWarehousing, 10,001+ employees

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SageMaker is useful as a managed Jupyter notebook server. Using the notebook instances' IAM roles to grant access to private S3 buckets and other AWS resources is great. Using SageMaker's lifecycle scripts and AWS Secrets Manager to inject connection strings and other secrets is great.
SageMaker is good at serving models. The interface it provides is often clunky, but a managed, auto-scaling model server is powerful.
SageMaker is opinionated about versioning machine learning models and useful if you agree with its opinions.

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Gavin Hackeling

Data Scientist

Wonder (AskWonder.com)Research, 11-50 employees

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Cons

You cannot as a novice just play around and get started. The learning curve is very steep, rewarding, but steep. I can't help but wonder if the product would not benefit from a "light" version for less data-mining accustomed business managers.

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Mika Silverman

Consultant

MarineXchange SoftwareInformation Technology and Services, 11-50 employees

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Amazon SageMaker is a great tool for a data scientist, although surprisingly, comparing different machine learning models with SageMaker is not as easy as one would think. I think Amazon needs to team up with a data scientist who does ensemble modeling.
Because SageMaker is targeted for machine learning models, other models a data scientist might use require more effort to get them incorporated. My guess is Amazon is moving to make SageMaker a more complete tool.
SageMaker can take a long time to run on larger data sets. That's the case with every big data science tool I've used, but SageMaker doesn't seem to be as quick as other tools.

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Thomas Young

Owner, previous CEO

Econometric StudiosFinancial Services, 11-50 employees

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Likelihood to Renew

Alteryx Analytics6.5

Based on 14 answers

The product fulfills business needs and it is a pleasure to work with the provider.

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Nick Lensing

Data Engineer

Virtual DBSMarketing and Advertising, 51-200 employees

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No score

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Usability

Alteryx Analytics10.0

Based on 2 answers

Through a graphical UI one can perform engineering and development, other vendors do not have such a code-less interface.

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Nick Lensing

Data Engineer

Virtual DBSMarketing and Advertising, 51-200 employees

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Reliability and Availability

Alteryx Analytics10.0

Based on 1 answer

I use many programs and compared to others, Alteryx virtually never goes down, freezes up or gives an application error. Over a 4 year time period that I have used this program, any of these may have happened 3 times. It is an incredibly stable program that I feel completely confident in.

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Dan Chapman

Manager, Market & Competitive Insights

Office DepotBusiness Supplies and Equipment, 10,001+ employees

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Support

Alteryx Analytics9.9

Based on 2 answers

Overall pretty good. Depending on the quality of the question posed the CS team will get back as they are available

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Nick Lensing

Data Engineer

Virtual DBSMarketing and Advertising, 51-200 employees

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No score

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Implementation

Alteryx Analytics10.0

Based on 1 answer

There is really not much to it (the installation, that is). Once you get it installed, along with any of the add-ons (demographics, R, etc.), you are up and running almost immediately. There is really no additional setup. You can immediately begin blending data, running demographics, performing spatial queries, running predictive analysis, etc. And for many of these functions, the learning curve is quite easy.

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Dan Chapman

Manager, Market & Competitive Insights

Office DepotBusiness Supplies and Equipment, 10,001+ employees

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Alternatives Considered

Alteryx and Tableau. That all you need

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Shaun Beckett

Data Analyst & Creative Integration

LS Direct MarketingMarketing and Advertising, 11-50 employees

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We have not invested in another machine learning software at this time and so far this has proved very successful with our machine learning teams. As mentioned, I am training these individuals simply on the fundamentals of the software and using it/customizing it for their needs. It has been very easy to do this and has gotten great reviews across the organization so far.

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Verified User

Employee in Human Resources

Real Estate Company, 1001-5000 employees

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Return on Investment

It gets the job done fast.
It lends itself well for people with a less-technical aptitude to understand the data process.
It empower the user to come up with any possible solution to a problem.

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Nick Lensing

Data Engineer

Virtual DBSMarketing and Advertising, 51-200 employees

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We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
For our use-cases, serving models is less expensive with SageMaker than bespoke servers.

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Gavin Hackeling

Data Scientist

Wonder (AskWonder.com)Research, 11-50 employees

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