Data is indeed proven to be a catalyst for progress. However, it needs training and expertise to make use of your data’s potential. It is not a small task to develop a data culture and encourage data competence at all business levels.
One of the main components of data analysis is data visualization. In an intelligible and visually attractive way, the data were always significant. Data visualization is one of the competencies that data scientists have to master to better interact with end-users.
The Tableau is the first term that ever comes to mind when you speak about data visualization. As Tableau has been increasingly adopted in the market, the demand for certification training is rising.
Also, Tableau is a growing skill. According to Burning Glass, open employment demanding Tableau skills will increase by 34.9 percent in the next decade, which gathers and analyzes millions of jobs worldwide. These are the top careers in which these skills are needed – data analysts, software developers, business intelligence analysts, data scientists, and financial analysts — all potentially valuable positions with many career upside.
There are several specialized learning paths associated with tableau roles in the company. Each position is designed to accelerate your people’s skills quickly and efficiently.
Role-driven Tableau eLearning today is the #1 most requested eLearning feature. The learning paths offer you an extensive self-paced, guided program through which you can easily integrate, extend and use the Tableau as quickly as ever.
Table of Contents
What is Tableau?
Tableau is a tool for business intelligence to evaluate data visually. An interactive and shareable dashboard that shows the patterns, changes, and density of the data can be generated and distributed by the users as graphs and charts. To acquire and process data, Tableau may link to files, relational, and Big data sources. The software enables data mixing and collaboration in real-time, which makes it very special. It is used to analyze visual data by companies, academic scientists, and several public organizations.
How to learn Tableau?
eLearning is the cheapest way to reliably and scalably train the Tableau users in your company. eLearning speeds up the onboarding process for new users and guarantees Tableau skills for experienced users. Content engagement and real-time reviews ensure that users retain the information. Detailed usage reports are available to administrators to track users’ progress and enable them to complete the course.
Learning paths avoid guesswork and provide a straightforward approach to ability. New lessons are periodically added to get the most up-to-date tableau-training material via eLearning. Assessments allow you to determine where your learning is and to recognize your skills. Tableau certification recognizes you for your success in your education and offers a way to demonstrate your expertise in Tableau.
eLearning helps you learn at a convenient rate anywhere, at any time. Find the skills you need with a comprehensive training library to get back to your analysis quickly. Don’t let your Tableau training stop. Both eLearning courses offer certificates and continuing education credit hours so you can pursue your eLearning courses to gain certifications and more.
Steps to use Tableau
To use Tableau, you have to follow this 3-step mantra:
1. Connect to data
In Tableau, the first thing you do is to link your data. Two connections are primarily available.
Link to the server or connect to your local file. You can connect Tableau to any local file or database, including Access, Excel, Text File, Statistical File, and other Database Files. Local connectivity has the highest data processing speed.
You can also link Tableau to your data server. It can bind to nearly any form of data server. Data may have live connections when operated on Tableau. Any changes in the source data are automatically changed in Tableau. However, data may be extracted to a Tableau repository so that any changes to the source data are not affected.
You can also merge various data sets to make better insights and links. Data sets are joined in different ways.
2. Play around with the UI
You can create visualizations within the pane and prepare different visualizations for reflecting the dataset. Some views are not possible due to incompatible data sets at times.
- The menu bar has many choices for editing your visualization.
- The file menu creates Tableau’s latest workbook and opens current workbooks both from the local and Tableau servers.
- You can use the data menu to create new data sources for analysis and visualization. You may also replace or update an existing data source.
- You can use the worksheet menu to build a new worksheet with different display features such as title and captions.
3. Create visualizations
The following table shows how you can choose the right visualization from several choices for your dataset.
- Bar graph – used for discontinuous dimensions
- Line graph – chosen for continuous dimensions
- Dual-axis graph – used for a combination of two actions
- Geographical graph – used for geographical map measurement
- Area graph (Dual axes) – shows a better comparison between measures.
- Heat map – used to view differences across categories.
- Treemap – used in nested rectangles to measure the quantity
Enhance your time to value with Tableau eLearning
Tableau is a groundbreaking data visualization tool. Tableau links to almost every data source such as data warehouse, Excel, database, and more. In a matter of minutes, it offers information in real-time.
Everyone who works with big data should certainly be equipped with robust data visualization software. You will save too much time not to spend the time and effort to understand it in the long run.
But Tableau is not the only tool for a database analyst or developer to learn. For instance, SQL is an excellent piece to remember. Soft skills are also needed because those working with the data often have to justify their result to others, including team members and managers.
Tableau training is vital for data scientists, analysts, and others interested in data analysis and visualization. If you think that’s all you have to advance your career (or landing a dream job as an analyst), consider winning one.
