Tableau

The Context for Aggregation An aggregate step in Tableau Prep is used to change the level of detail of data so it’s less granular, often in preparation for being combined with other data at a higher level of aggregation. How to Aggregate First, we need to add an aggregate step in the flow. Click the plus on the previous step and select Add Aggregate. The aggregate pane opens below, allowing us to configure this aggregation. On the left, we see the list of fields in this data source. On the right, we have two drop areas, one for grouped fields and one for aggregated fields. In order for a field to “come out the other side” of an aggregation step, it must either be grouped or aggregated. Grouped fields determine the granularity of the row. If we want our post-aggregation data to be the number of books sold per date, we would group by book and date. If we want our post-aggregation data to simply be the book (which we do), we’d group only by book.

The Context for Pivoting If your data has multiple fields for the same attribute, or if there is unique information stored in the field name (such as the fact a given book is on the Hardcover Nonfiction bestseller list), your data may need to be pivoted. In our example, we have a week’s worth of bestseller data that has multiple fields all containing the same information about the bestselling books. Additionally, the field names are the bestseller lists. To analyze this data effectively, we need to pivot it so we have a column for book information and a column for bestseller list.

The Profile Pane When we’re on a cleaning step, indicated in the flow by the bar icon, the pane below the flow is the Profile Pane. (For information on cleaning data, check out the video on the Cleaning Step.) The Profile Pane helps us explore our data and understand its contents--it’s a powerful way of interacting with our data. For discrete data, each grey bar we see represents a value in the field itself. The length of the bar represents the number of records with that value, and the visual scrollbar provides an overview of the distribution of the data. For example, we can see that most titles show up only once in the data, but Ready Player One appears twice. Similarly, most authors appear once, but we can sort and bring the authors with the most records to the top. 

The Context for Group and Replace A common issue in data cleanliness is the presence of multiple values that should be a single value, such as GB and Great Britain. To deal with this in Tableau Prep, we can leverage the Group and Replace feature in a cleaning step. This feature allows us to group multiple values and replace them with a single value--essentially re-aliasing. To begin, we’re on a cleaning step in the flow. In the profile pane, we can see the fields in this data set. This is clearly nonsense data to illustrate a feature, not data we should try to analyze. Manual Grouping --- you can add a data which is not already present as well(used when data is irregular and doesn't follow a pattern.) Pronunciation  - uses phenotics - metaphon 3 algorithm (used to catch misspellings) Common characters

The Context for Cleaning Data can be unready for analysis for a lot of reasons. If you need to do things that have nothing to do with shaping the data (like pivoting or aggregating) or combining it (through joins or unions), then it’s likely you’ll need to perform some cleaning operations. Cleaning in Tableau Prep covers everything from removing fields, changing data types, creating calculated fields, and more. How to Clean Cleaning data in Tableau Prep is done in a Cleaning step in the flow. From the previous step, click the plus icon and choose “Add Step”. The “ default ” step is a cleaning step, which appears in the flow as a bar. When we’re on a clean step, below we see the profile pane and data grid. Each field in the data is represented as a card in the profile pane. We can rename fields or change their data type by interacting directly on a card. If we open a card’s menu, we see many other options. Let’s go through brief examples of each of these. Remove Field : First...