Alteryx Analytics Reviews

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.

Alteryx Analytics is very well-suited for areas like data analysis, designing dashboards, embedding basic mathematical models in the system and establishing data driven decision-making across the firm. In areas like healthcare, finance, insurance, banking, sports, etc where we have immense amounts of data, Alteryx can play a major role in helping people opt for a data-driven decision mindset.
It might not be a very good solution for areas like ETL (Extract Transform Load). It would be interesting to see if Alteryx diversified in that area as well.

Alteryx is best used for corporations that rely on large excel files and have too many reporting tasks to perform everyday. It will make repetitive tasks to run through just one click. It is also recommended for initial predictive analysis such as forecasting, demographic analysis and behavior analysis. Since it's compatible with "R", it adds even more functionality.

Operations, business intelligence, Supplier performance, logistics, production bottlenecks. Essentially any case where information across departments is needed, we really see Alteryx being the go-to for objective dialogues. Previously, these departments were having subjective narratives on how to solve business problems, because the data was too difficult to connect and makes sense of. With Alteryx, the focus is on "What does the data show that are good options to change a business process?"

Pulling data from databases and preparing for data visualization is our primary use for Alteryx, however if you have perfect data, Alteryx can get redundant, but honestly who has that.

Alteryx Analytics is suitable for less technical users who do not have coding experience, you can gather information rather painlessly; however, it is still not quite as good as using a language such as Python or R to integrate your advanced analytics work.

Well suited: if an organization already has a lot of running ETLs or pipelines but need to systemize them, Alteryx is a good choice. It would be good to figure out how well Alteryx would be harmonized with the existing components, but in a general sense, it may be well harmonized.

Less appropriate: Alteryx is good for "automation", but some data developers and analysts may prefer to remain and keep using SQL tools. One should be careful of not just adding "one more layer or tool" into the existing pipeline and make it more complicated to manage.

More often than not, Alteryx can handle any situation or scenario thrown at it. Some may take a little more "trickery" along the way, but for the most part it is fairly easy to get from point A (data) to point B (results/report). And the nice thing is is that there is more than one way to produce the same result - two people with two different mindsets can ultimately create the same thing, but do so in a way that is better suited for their skill level.

It is very well suited for mid-sized data operations. One person working on a project is ideal. I have not used Alteryx in a collaborative project, so can't say for sure. It is quite powerful and compares well with the competitors. If you have data from disparate sources, it helps to have a tool like Alteryx.

Alteryx can do so much more than I use it for, so I believe the only case where Alteryx wouldn't be needed is when a department/team had a full development team to prep data pre-analysis or already has a central data store fully stood up and standardized. Alteryx works extremely well with a multitude of BI and database solutions and would be a great fit for any team trying to speed up the typical daily grind of data prep and ETL so their analytics and data team can be more agile, accurate, and automated.

Most suited: Teams involved in BI and reporting can do data analysis, blending and analysis really quickly as well as do the statistical analysis and expand the horizon of analytics into the organization with ease.

Less appropriate: Organizations that have low analytics adoption and more of visual report consumption culture would find it difficult to resonate with the value proposition of Alteryx.

I know I have stated this already, but it really is very helpful for blending data from different sources. [It's] great where the people using it do not know coding. Love the drag and drop options. Makes life really easy. Could be a hassle trying to learn it for the first time due to the quality of training videos. It is improving a lot day by day and I love the way they are going with the product.

Alteryx is great at doing complex manipulations like filtering out the data and summarizing, without writing a single line of code. Also, publishing on Tableau Server is a great feature where we can use it as a source in Tableau.

Alteryx is suited for many, many use cases and scenarios - too many to mention.

It is great for dealing with mass quantities of data, not so good if you're trying to analyze. If you're dealing with 50k+ records, then it probably is considerably faster to deep-dive into the data with Alteryx. However, for anything under that, Excel is the better program for visually finding patterns and trends in data, at least for someone who has a limited tech background.

Ask about documentation, maintenance and support.

Great for working with huge sets of data (and small sets too). Very well suited for geographic and data analysis. Fantastic for combining data from multiple sources into one and writing data and reports out to Excel, PowerPoint, Access, text files and even several GIS platforms. It is easy to write out data to multiple files/slides/databases (and I'm talking thousands of files if necessary). Can produce great looking maps when the time is put in. This program would not be appropriate for companies with only small datasets. The program can be expensive but I understand that they recently tiered their products at different price levels.

I am admittedly a Customer Evangalist for Alteryx and believe that Alteryx should be considered as a solution enabler in most cases. Alteryx allows for connection to data of many types and sources. If Alteryx complicates or lengthens the execution time of a process because of the need to move data from one point to another, I'd likely rearchitect the solution.

Call Alteryx and see how quickly they respond to your needs. Client Services is available most hours either by phone, email or chat. You can post to their community boards. They are very responsive and seek high customer satisfaction. They are very accessible and if you want to talk to their Chief Customer Officer, she'll get on the phone with you.

When working with a lot of data where processes will be repeated in a similar fashion it is a must have. It cuts down on re work and gives the user the option to re-use past work in order to focus on more important theoretical aspects of the project. For one off formatting or similar tasks it might still be better to utilize other tools. PS SQL and R are two good programs to have a working knowledge of while working in Alteryx.

I wouldn't use Alteryx to do a lot of reporting, but thanks to its integration with Tableau, that is covered. Still the best BI data blending software out there.

It is a great departmental solution.

Alteryx is best suited for analytical departments, mapping/GIS teams, and data teams that need to manipulate data. It is less equipped to be the all around solution if you're looking to make very impressive reports with very customizable maps. But generally speaking, it's very useful and expected to continue to capture a larger audience over time.

It is well suited where the user likes to write some code from time to time and also in cases where machine learning is required. Alteryx uses R for its machine learning which makes it life easier. Scenarios where maps need to be created for visualization are the examples. It lags a lot compared to other similar softwares for visualization but is very friendly for data analysis.

It is well suited if you have a use case of huge amounts of data needing to be mapped out or performing analytics on it.