Overall Satisfaction with Alteryx Analytics
We use Alteryx to make decisions on the large datasets from a disparate set of sources. Alteryx lets us join data from various sources and perform operations. We primarily use it to gather data from various CRM systems. We use this data to make decisions on the impact of marketing campaigns and also to inform the sales team about client engagement which helps the sales to get leads.
- To get data from various disparate sources and to have a holistic view of the marketing activities.
- To provide sales with leads weekly or monthly based on their marketing engagement.
- To analyze the CRM systems like Pardot & Salesforce to create a list of customers for targeted email campaigns.
- Though it provides good data blending functionality, the visualization aspect is missing. For visualizing data you need Tableau or Power BI.
- They have some shortcomings like when reading similar files. The tool figures the datatypes randomly and a integer data type might be read as text, and then the tool is unable to read data. There is a way around this but it's cumbersome.
- The API connections are limited at this point. They do have a macro which you can create to connect to any API, but it's not very straightforward.
Alteryx has a better interface than KNIME, though it's a bit more expensive than KNIME (an open source tool). We cannot use open-source software due to data privacy issues, and this is why we selected Alteryx. Alteryx also had an agreement with Macquarie and provided a discount on the purchase of ~10 licenses.
Alteryx is well suited for joining data from disparate sources. The data should be in a continuous format. In most situations, there should be a common field between various datasets. It can help to provide an overview of systems and create reports for senior management. It can also connect to back end data repositories and collect information. It can also read large sized spreadsheets in a matter of seconds.