Nevertheless, two additional transformations are needed in order to leave the dataset ready to train models (transform the categorical variables into a numerical format of 1 and 0 to finally normalize them). At this point you can add an output process that would apply all changes to the dataset and export the result in CSV format or as an extract from Tableau Desktop to create reports. As can be seen, all steps could be performed in a minimum effort with a set of clicks and Tableau Prep has fulfilled its functionality (clean the data before creating reports with Tableau Desktop). Up to this point the dataset is completely clean and can be used for pattern analysis and reporting. Section 4: Adaptation of the dataset for modeling The formula used in the calculated field was: IF ISNULL() THEN ELSE ENDįinally, the column transformation process ends with the elimination of the field with the passenger ID and ticket number (Similar to the Cabin elimination step). To do this, I decided to replicate the cleaning process that I once did in Python to the popular Titanic dataset being careful to the point where the tool may fall short and if it is really compliant enough to apply to a larger project.Īgregation and Join steps in Tableau Prep As a consultant of this tool, I was then in the duty to explore its potential, to know its advantages and its real capacity in order to evaluate if it is viable to present it to the clients within their BI projects. Regardless of the recent changes, Tableau has made to its Tableau Desktop product in order to improve performance with large volumes of data, in most cases, it is necessary to add an ETL process such as Talend or Pentaho prior to analysis and reporting with Tableau Desktop.Ĭonscious of the previous, last year (2018) Tableau released to the public the product Tableau Prep Builder with the intention of providing a Drag & Drop tool prior to data exploration with Tableau Desktop. In my job as a BI consultant with Tableau, I’ve heard quite a lot of the phrase “Tableau is not an ETL” where I’ve had to agree most of the time.
For more information, click here.Tableau Prep, how powerful it is, where it fails and where its greatest advantages lie. I understand that these countries may not have the same data protection laws as the country from which I provide my personal information. In particular, I consent to the transfer of my personal information to other countries, including the United States, for the purpose of hosting and processing the information as set forth in the Privacy Statement. I agree to the Privacy Statement and to the handling of my personal information. By submitting this form, you confirm that you agree to the storing and processing of your personal data by Salesforce as described in the Privacy Statement. By submitting this form, you acknowledge and agree that your personal data may be transferred to, stored, and processed on servers located outside of the People's Republic of China and that your personal data will be processed by Salesforce in accordance with the Privacy Statement. Read on to learn more about these new and improved features.īy registering, you confirm that you agree to the processing of your personal data by Salesforce as described in the Privacy Statement. To make it easier to work with text files that contain strings of data values in a single column, Tableau Prep will help identify and suggest fields that should be split. When new fields are added, Tableau Prep detects them and adds them to your pivot for you if they match the pattern.Īdditionally, in this release, you can now add descriptions for every change that you make, not just the entire step. In this release, you can now also use wildcard pivot to find, match, and pivot field values in your dataset.
But that’s not the only improvement for pivoting your data. With over 100 votes, this is one of the highest requested Tableau Prep features on the Ideas forum. In the January release of Tableau Prep (2019.1.1), you can now pivot your rows to columns (sometimes called unpivot). Happy new year from the Tableau Prep team! After nine releases in 2018, we are kicking off 2019 with new features requested by the Tableau community.
0 kommentar(er)
