Tableau is a powerful Data Visualization tool that data analysts, scientists, statisticians, and others may use to visualize data and draw clear conclusions from data analysis. Tableau is well-known for its ability to process large amounts of data quickly and produce the necessary Data Visualization results.
In this article, you will learn about Tableau and how to DateParse Tableau and convert fields to Date type.
Table of Contents
Tableau is a powerful and rapidly evolving Data Visualization program. It aids in the conversion of raw data into an easily understandable format. Tableau assists in the generation of data that specialists at all levels of an organization can understand. Custom dashboards are simple to create even for those with little technical skills.
Tableau allows for quick Data Analysis and the creation of graphics in the form of dashboards and workbooks.
Key Features of Tableau
- Usability: It’s easy to use and doesn’t require any technical or programming knowledge. When it comes to constructing a dashboard, it responds quickly. Tableau may be downloaded to mobile devices and desktop computers, making it easy to access and analyze data. Multilingual data representation and real-time data exploration are supported.
- Connection and Sharing: It comes with many advanced features, such as cooperation and data distribution.
- Security: Multiple data sources are linked together in a highly secure manner. Importing and exporting massive amounts of data is simple.
- Advanced Visualization: Tableau allows you to create a wide range of visualizations, from simple Pie Charts and Bar Graphs to more complicated Histograms and Gantt Charts.
Hevo Data, a No-code Data Pipeline, helps load data from any data source such as Databases, SaaS applications, Cloud Storage, SDKs, and Streaming Services and simplifies the ETL process. It supports 100+ Data Sources (including 40+ Free Sources) such as Tableau. It is a 3-step process by just selecting the data source, providing valid credentials, and choosing the destination.
Hevo loads the data onto the desired Data Warehouse/destination in real-time and enriches the data and transforms it into an analysis-ready form without having to write a single line of code. Its completely automated pipeline, fault-tolerant, and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. The solutions provided are consistent and work with different BI tools as well.
GET STARTED WITH HEVO FOR FREE
Check out why Hevo is the Best:
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled securely and consistently with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
Simplify your Data Analysis with Hevo today!
SIGN UP HERE FOR A 14-DAY FREE TRIAL!
Understanding the Process of Verifying Date Fields
A Date Field might appear as a string in either the Data Source page or the Data Pane.
All of the advantages and conveniences of dealing with date fields, such as drilling down, using date computations, and toggling between Continuous and Discrete measurements, are lost when dates are treated as strings.
If the dates are not parsed correctly then perform the following steps in order:
DateParse Tableau Process: Change the Data Type of the Field
Ensuring the data type is set to Date or Date & Time is the first step in fixing a date field interpretation in DateParse Tableau.
- Step 1: In the Data Source or Data pane, click the data type icon and change the data type to Date or Date & Time.
- Step 2: Examine the data in the Data Source or View pane. If there are a lot of null values, change the data type to String and continue. To fix the problem, use the DATEPARSE function to make a calculation.
DateParse Tableau Process: Create a Calculation Using the DATEPARSE Function
Dates can be saved in an almost limitless number of forms. Years come before months in some date fields, periods divide sections of the date in others, and still, others employ a mix of styles. It’s possible that Tableau can’t comprehend a date field because the format can’t be translated.
You may explicitly identify which portions of your field are which parts of a date using the DATEPARSE Tableau function. In other words, you’re making a map that Tableau can utilize to convert the string to a date field. This map is called The Format.
DateParse Tableau Calculation Creation: Creating the DATEPARSE function
To create a DATEPARSE Tableau Function, follow the given steps:
- Step 1: Examine your date field’s current format. In your field, take note of where the months, years, hours, and days are shown. This information is required for the DATEPARSE Tableau function.
A- Day of month
D- Hour, minute, second, millisecond, period
- Step 2: In the Dimensions pane, right-click the date field and then choose Create > Calculated Field.
- Step 3: Write the DATEPARSE function in the dialogue box. The format and the string are the two pieces of the DATEPARSE Tableau function. The string represents the field you want to convert, and it must be of the string data type.
Tableau will use the format as a reference to interpret the string as a date. As shown in the table below, each portion of a date or time string has a corresponding symbol. The format should be identical to the way the date is shown. The calculation may yield null values if a single year code (“Y”) is used when the text has a two-digit year code (“97”).
To accurately read the string, the format must include all spaces, hyphens, and other non-alphanumeric symbols.
DateParse Tableau Calculation Creation: Date Field Symbols
|Date Part||Symbol||Example String||Example Format|
|Year||y||97, 2017||yy, y or yyyy|
|Year of “Week of the year”||Y||1997||Y|
|Time Zone||Z, z||-0800, PST-08:00, PST||Z, ZZZZ, zzz|
|Month||M||9, 09, Sep, September||M, MM, MMM, MMMM|
|Week of the year (1-52)||w||8, 27||w, ww|
|Quarter of year||Q||Q2, 2nd quarter||QQQ, QQQQ|
|Day of week||E||Mon, Monday||EEE, EEEE|
|Day of month||d||1, 15||d, dd|
|Day of the year (1-365)||D||23, 143||D, DD, DDD|
|Period (am/pm marker)||a||AM, am, PM||aa, aaaa|
|Hour (1-12), Hour (0-23)||h, H||1, 10, 16||h, hh, HH|
|Minute||m||8, 59||m, mm|
|Second in a minute||s||5, 05||s, ss|
|Fractional second||S||2, 23, 235, 2350||S, SS, SSS, SSSS|
|Milliseconds in the day||A||34532||AAAAA|
- Step 4: Compare your format to the string shown in Tableau. Select OK to create the new calculated field if the symbols and formatting are right. In your view, the calculated field will be used as a date field.
DateParse Tableau Calculation Creation: Hyper Extracts
The Unicode Consortium defines the symbols for .hyper extract data sources. Go to Format syntax in the DATEPARSE function to extract data sources for more information on the field types and symbols that can be used with the DATEPARSE Tableau function in .hyper extracts.
DateParse Tableau Calculation Creation: Locale Considerations
To interpret and display the strings you want to convert, the DATEPARSE function uses the locale supplied by your computer settings. The location, in particular, has an impact on whether or not a particular format may be identified. This means that if the locale doesn’t support a format, you can get a null value or nothing at all. For example, you’ve got the following string in your data:
The DATEPARSE function returns different values for this string depending on the locale. You will receive a particular value in the English locale, but none in the Japanese locale. Because the Japanese locale does not recognize “Sep,” no value is returned in this example.
|English locale||Japanese locale|
|#9/12/2016 9:08:09 AM#||–|
When you use the DATEPARSE function to convert a string to a DateTime type, Tableau will show the DateTime value in the default format of your locale, just like it does with all dates. The result of the DATEPARSE function may display your new DateTime value in a different format if the locale changes.
DateParse Tableau Process: Create a Calculation Using the DATE Function
You can use the DATE function instead of the DATEPARSE function if the data you’re working with doesn’t have the DATEPARSE function or if the field you’re trying to convert has a numeric data type.
- Step 1: The DATE function converts a date type from an integer, string, or date expression. Tableau inserts a new field in your Tableau data source when you use the DATE function in a calculation. This field allows you to interact with your date data as a date. Tableau must be able to interpret the components of the string into date parts in order to effectively output date values from an integer, string, or date expression using the DATE function. Tableau uses the computer locale to determine the date’s default format after identifying the date’s components.
For example, the table you’re dealing with has a column called “Original Date” that contains date data. The column “Original Date” is of the string type.
- Step 2: In this situation, you may build a calculated field named “New Date” that converts the string values in the “Original Date” field to date values using an expression in a DATE function.
- Step 3: The LEFT function isolates the day component, the MID function isolates the month component, and the RIGHT function isolates the year component in this example’s date expression.
DATE (LEFT([Original Date], 2) + "/" + MID([Original Date],3,3) + "/" + RIGHT([Original Date],4))
The “New Date” calculation gives the following column:
The updated date values in this example are based on an English locale and default formatting.
You have successfully learned how to convert other fields into the Date field in Tableau in this article step by step. You learned of two ways to do this: Using the DATEPARSE and DATE Functions.
However, as a Developer, extracting complex data from a diverse set of data sources like Databases, CRMs, Project management Tools, Streaming Services, Marketing Platforms to Tableau can seem to be quite challenging. If you are from a non-technical background or are new in the game of data warehouse and analytics, Hevo Data can help!
Visit our Website to Explore Hevo
Hevo Data will automate your data transfer process, hence allowing you to focus on other aspects of your business like Analytics, Customer Management, etc. This platform allows you to transfer data from 100+ multiple sources to Cloud-based Data Warehouses like Snowflake, Google BigQuery, Amazon Redshift, etc. It will provide you with a hassle-free experience and make your work life much easier.
Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand.
You can also have a look at our unbeatable pricing that will help you choose the right plan for your business needs!