Tableau

What differentiates Tableau from other similar products?

Tableau provides an emerging solution in terms of data analysis in companies that allows us to analyze and compare in a faster way all our big data, resulting in better decisions based on the study of the different variables presented in our reports. Tableau allows us to create a narrative story with all the data that we provide in addition to ordering them in lists, tables, charts, thus greatly helping the development and saving time for our company.

What is your favorite aspect of this product?

Excellent graphics based on the organization's data, well defined and with accurate information. It is possible to import files from different data sources such as Excel, Google, among others. The interface is quite nice and very ergonomic, which is a great advantage when performing tasks.

What do you dislike most about this product?

Price is quite high, although its functionality is quite good I think they should lower the costs a bit. Sometimes it is difficult to select the criteria for the information we need making us lose a little time. Difficult to configure, users must be well oriented and trained otherwise the software can not be used correctly and can not take full advantage.

What recommendations would you give to someone considering this product?

Better technical support as it is a bit difficult to understand at the beginning, service costs are still a bit high, after that the tool works quite well, there are no major recommendations to make as soon as it was implemented we started to get excellent results in terms of data analysis. It is a software that adapts excellently to any part of the world due to its interactivity.

What differentiates Tableau from other similar products?

Anyone using Tableau in the data science field immediately understands this. The numerous import options for all types of data are truly astounding. I can import data from my Microsoft database and create management dashboards, or I can import a simple 3 GB CSV file from the sales department. One can't really pick here very much. We create dashboards for higher management. Here, among other things, sales results are taken into account, and forecasts and other analyses are produced using Power BI's provided graphics. The reports in PDF are a good addition because we can quickly make them available and they work well for mass printing.

What is your favorite aspect of this product?

the essential selection of features and choices. Large data sets can be perfectly prepared for analysis and visualization with Tableau Prep. Numerous analyses move quickly and can be finished in a few minutes. LOD (especially for cohort analyses of customer data), Gruppieren/Aliasse/Hierarchie (to keep track of things when there are many dimensions or numbers), and Parameter are features that I frequently use. Regarding visualization, I especially value the capability to combine various diagrammtypes and quickly create very dynamic visualisations. Draw conclusions and present them using data analysis based on a range of data sources ERP.

What do you dislike most about this product?

Fundamentally, in order to utilize the full range of options, some topics (such as filterreihenfolge, LODs, etc.) require some initial work. What I still lack is a quick way to create beautiful dashboards and also, for example, a way to unify different dashboard designs (for example, adjusting the font size. Whoever switches from Power BI to Tableau has a problem because DAX commands are sadly not supported. Unfortunately, using Tableau's own language solution requires some extra work. However, because it involves logical English terms combined with commas, our division was a little confused when it was first implemented.

What recommendations would you give to someone considering this product?

I use Tableau as a business intelligence tool for ongoing reporting as well as a quick-and-dirty analysis tool (zB Monatsdashboard). I use the tool specifically for the analyses listed below: Customer journey or conversion funnel analyses in the context of digital marketing, such as in relation to revenue data, creating management dashboards based on existing databanks and investigating previously unexplored datasets as part of a business analysis. I use Tableau Desktop to visualize data sets from customer data banks as well as to visually prepare other values for people who have less statistical knowledge.