![]() ![]() Organizations need predictive models built and automated for forecasting or predicting future results, failures, sales, etc.Analysts need to be able to answer geospatial questions (distances, trade areas, drive times, geocoding). ![]() Analysts need the power to do complex data mappings and manipulations.Manual data processes need to be automated and documented.Data requires clean-up before it can be passed to a business intelligence tool.Data needs to be accessed, integrated, and consolidated from many locations (files, databases, cloud/REST API).Just because it’s possible doesn’t mean it’s a good idea. Be careful you don’t buy a screwdriver to pound nails. There is some overlap, and the vendors will try to blur the lines. Tableau consumes data from ERP, CRM, Alteryx, Excel, data warehouses (Snowflake, Redshift, Vertica, Azure). Tableau is fantastic at data visualization, dashboards, online consumption, and distribution of information.Īlteryx fetches data (from anywhere), manipulates it, and feeds that data to Tableau, Power BI, Excel, data warehouses (Snowflake, Redshift, Vertica, Azure).Alteryx is fantastic at data access, clean-up, blending, manipulation, Excel process automation, and process documentation.For those of you with a short attention span, here is a summary: In the pages of analysis that follow, you’ll find many examples of what each of the tools do well, and where they lack functionality. We’re asked about Alteryx vs Tableau frequently, so we’ve written up our findings to help you understand the two solutions better. Once we dig into the organization’s challenges and existing technologies, we can help pretty quickly. Cognos School District Analytics: PowerSchool K-12Ĭlients ask us to help them choose between vendor solutions nearly every day. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |