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Today’s world runs on data. There are useful trends and patterns hidden in the vast amount of data stored in organizational databases. Understanding the hidden information can help companies and individuals grow, change their working strategies, and so on. Tableau is one of the popular tools available that can create interactive visuals from data without the need to code. It converts large amounts of data into charts, maps, and stories that are insightful and easy to understand. Data blending is one of the focus features of Tableau. In this blog, we will explore what is data blending in Tableau, its definition, examples & benefits, and what to look for when choosing a Tableau course.
Tableau is highly sought after because it can be connected seamlessly with many data sources like Excel sheets, databases, workbooks, etc. Thus, it can act like a centralized space from where all data related to an organization can be managed. Whether a beginner or an experienced analyst, Tableau’s user-friendly interface and powerful features can help in Data Analysis by finding patterns and trends hidden within large amounts of data. This data can then be used to drive changes in the organization.
Data Blending – Combining Data
Data analysis often requires combining information from different sources to create elaborate reports. There are two ways to combine data in Tableau – data joining and data blending. Data joining is useful when combining data from the same source, like from within the same database. When data from two different sources are to be combined, data blending is used. It allows you to easily merge data from multiple sources, providing a single visual of the data. Whether you are an analyst, a business professional, or just someone interested in data analytics and visualization, understanding data blending in Tableau can improve your analytical capabilities.
Traditional data integration techniques merge data at the database level. However, data blending allows you to combine data directly within Tableau. This helps in maintaining the original data sources separately.
How Does Data Blending Work?
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Data blending involves a primary data source and one or more secondary data sources. Tableau uses common fields to blend the data. Let us consider an example to understand how data blending is done. A retail store has Sales data and Customer data. The Sales data contains information on sales, such as customer ID, date of purchase, product details, and amount. The Customer data includes customer details, like customer ID, name, and region. They want to create a report showing sales by customer region.
Following are the steps to blend these two datasets in Tableau.
Step 1: Connect to Your Data Sources
Start by connecting to the data sources you want to blend. You can do this by bringing the fields from the data sources to Tableau. The primary data source is the one whose field you bring in first. The other one will be the secondary data source. The secondary source must have a “linking field” with the primary source. In the above example, if Sales data is the primary source, then, Customer data will become the secondary source.
Step 2: Identify Common Fields
Data from the two sources can be blended if there is a linking field icon. This means, there should be at least one common field with the same name in the data sources. A common field means a common dimension in the data sources. Determining this will serve as the key for data blending. For our retail company, Customer ID is the linking field.
Sometimes, there can be common fields, but they may not be named the same. Without a common field, data blending cannot happen. However, renaming one of the dimensions or manually defining a relation between the dimensions are ways to solve this problem.
Step 3: Create the Blend
Use Tableau’s data pane to link the common fields between the primary and secondary data sources.
Step 4: Build Your Visualization
Once you blend the data, you can use it to create visualizations as if it were a single, unified data source. For the retail shop, blending the datasets can be used to analyze sales performance across various regions, without combining the data externally.
What Are The Benefits of Data Blending?
- One of the most important benefits is the integration of data from many sources without the need for complicated processes. As a result, combining data for analysis becomes easier and faster.
- As the analysts work with multiple data sources at the same time, it enables them to perform real-time data analysis. Hence, they can make timely decisions.
- Moreover, analysts can capture any changes in the source data easily because data blending does not alter the original datasets.
- Furthermore, Tableau’s user-friendly interface makes data blending possible for people with little technical expertise.
What is The Scope of Learning Tableau?
Various industries widely recognize and use Tableau. Consequently, working knowledge of Tableau is a valuable skill for job seekers. The tool is versatile and is used across various fields. As a result, your Tableau skills can get you jobs in finance, healthcare, retail, marketing, etc. Tableau Certification programs provide structured learning. Moreover, employers highly regard these skills, and certification validates them. Furthermore, it can improve the chances of earning a higher salary than your peers.
Consider these factors while choosing a Tableau course
Here are some key factors to consider while looking to learn data blending in Tableau:
1) Course Curriculum
Look for a course that covers basic to advanced Tableau features. The course should include projects and working with real-time datasets that allow you to apply what you learn in class.
2) Qualified Instructors
Before joining, you should check the trainer’s background and experience in Tableau and data visualization.
3) Resources
A good institute should provide support and resources, such as access to a community of learners and additional learning materials like tutorials and guides.
4) Renowned Institutions
Choose a course offered by a well-known institute like Henry Harvin, They will have credible courses and certifications.
5) Reviews
Last but not least, check reviews from past students. This feedback can tell you about the quality of the course and also how effective it is.
Learn What is Data Blending in Tableau with Henry Harvin
After understanding what is data blending in Tableau, its applications, and how to choose an effective Tableau course, it will be easy to choose the right institution. Henry Harvin offers a Tableau Course online. Henry Harvin is an award-winning institute. Moreover, the Govt. of India recognizes them. When you enroll in this course, you become a gold member of the Henry Harvin Data Science and Analytics Academy. The institution offers placement support through placement drives, a job portal, and personalized job consulting.
Key highlights of the course
- Comprehensive curriculum
- 32 hours of sessions led by experienced instructors who are industry experts
- 11 hours of live doubt-solving sessions
- 192 hours of self-paced learning
- Real-time Tableau training projects
- More than 8 industry case studies
You can choose this course from the several courses in Tableau offered by Henry Harvin. You will have access to learning materials and recorded sessions of the classes. Additionally, Henry Harvin offers soft skills development and resume writing sessions for the all-round development of the learners.
You may reach them at +91 9899577620 and [email protected].
Conclusion
Data blending is an effective feature in Tableau that combines data from multiple sources easily. Then, it creates a visual representation of the combined data. This helps in understanding the information carried by the dataset, which in turn, helps companies make informed decisions. With Tableau skills, you can find roles in various industries like finance, healthcare, and marketing. If you are interested in learning Tableau, you should choose a reputed institution like Henry Harvin, which has qualified trainers and offers real-life projects. Furthermore, the availability of learning resources and certification options are also important.
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