Companies function in a highly competitive space where data is the key enabler of business transformation. As businesses vie for top space, they want to look at innovative ways to churn the available information and combine it with external data like social media and applications in real-time, for insights that can give them a business edge. They want a unified view of data using Business Intelligence (BI) tools for reporting, analysis and forecasting. Companies are thus using cutting-edge tools like Tableau for meaningful insights in real-time dashboards, for access to immediate analysis and modeling. The power of Tableau for reporting and visualization in real-time, and unlocking the wealth of big data is already established across industries and government sectors.
If you want to unlock your inner mojo for creative data analysis, or add to your analytical learning curve, then take a Tableau course. Register to learn the powerful BI tool that every researcher, analyst and marketing head swears by, and empower your data analysis toolkit.
Tableau: A platform, analytics software or BI tool?
Tableau is a platform for analytics and visualisation. It transforms raw data into a simple-to-understand and process visual format. It is a fully featured software that allows complex data visualizations and visual analytics for dashboard-style storytelling of your data. Graphs, charts, maps and colourful tables are customised to represent data in an aesthetically pleasing way that can be understood by any user in the organisation.
As a powerful BI tool, Tableau’s intuitive visualization allows you to analyze, manipulate, sort and filter your data, even create a wide variety of customized visualizations on the go. The visual presentations allow you to see what you may have missed with lengthy spreadsheets and reports.
What’s more, Tableau can work with a small quantity of data as well as terabytes of big data. It connects and pulls data from almost any platform, whether simple excel or PDF, or a complex database like Oracle, or in the AWS cloud, and stitches all this data visually for analysis and manipulation.
Tableau is a whole lot of things designed to suit all your data needs: a platform, software, and BI tool, all rolled into one!
Why is Tableau popular
The popularity of Tableau in recent years can be attributed to the following:
- Imports data of all sizes and ranges.
- Manages metadata.
- Translated queries to visualization in minutes.
- Blends datasets in real-time.
- Can be used by any non-technical user, as no technical skills or coding expertise is required.
- Supports real-time collaboration; it can filter, sort, and study data on the fly with live interactive dashboards.
- Not industry-specific, and can be used by a variety of industries including finance and healthcare.
- Works on all types of devices, no specific hardware or software support are required.
- Lends itself to spatial analysis, big data analytics, and AI integration for deeper insights.
- Well suited to the government and social sector where quick data visualization supports data-driven decisions on the move.
What is Tableau Analytics
As an end-to-end data analytics platform Tableau helps you to prepare, analyze, and share your insights, even using streaming data in real-time. Its built-in self-service visual analysis, allows users to ask questions, discuss and collaborate on insights and easily share those insights across the organization.
Tableau’s analytical capabilities facilitate the discovery of trends, patterns, and correlations in large amounts of raw data. The tools apply statistical analysis techniques to large datasets for powerful data analysis and dashboard visualizations for seamless data-driven decisions.
Who is a Tableau Analyst
The Tableau Analyst is a Data Analyst or a BI Analyst skilled in the various functions of the Tableau software.
The Analyst leverages Tableau to better understand the information available and share it in a useful format through dashboards. Tableau Analysts perform a critical role in the success of their organizations, making this a highly sought-after job role.
As per the Tableau official site, a Tableau Analyst is responsible for supporting the organization’s business to deliver valuable insights from data.
The Analyst questions the data sets, and provides directions to the stakeholders based on the interpretations. Mathematical and statistical concepts are applied to summarise, aggregate, synthesize and interpret the data. An understanding of different data structures and storage methods, and how data relates to itself is required for creating the relationships is used to present them visually. The Analyst retrieves data from databases, creates joins, and aggregations to custom-create data models for analysis and sophisticated visualizations.
Analysts are skilled in various testing techniques, such as simple A/B testing, modeling (fit and describe the data), ANOVA (analysis of variance), hypothesis testing, and more.
The Tableau Analyst is proficient with the Tableau Desktop to create different views and combine visualizations in the dashboard using the built-in features. A good Analyst leverages the “show me” feature to create customized content that breaks down complex business questions into smaller, consumable parts for instant understanding of the critical data elements.
As the Tableau Analyst needs to be a good visualizer to present the data attractively and simplistically, he is data-literate besides having a good eye for visual presentation. Various chart types in the Tableau platform are used to present the data manipulation and analysis. Attributes like size, position, and colors, are used for graphical layouts and visual appeal. A good Tableau Analyst does all of this to highlight key metrics in the data and to maximize understanding. In a nutshell, he is a multi-functional data analyst, crunching disparate datasets and juggling charts to find the right answer to the most common business questions.
Responsibilities of the Tableau Analyst include:
- Creating reports and dashboards for the stakeholders to consume or iterate on.
- Performing ad-hoc data exploration to underscore business opportunities.
- Conducting meaningful data analysis for informed decisions.
- Presenting data in granular details, with add-on expressions and interactivity to grab the interest of the user and help decisions.
Reasons to learn Tableau
Data Analysis is not just about being a part of a dynamic data-driven environment. It is also about knowing the right software and analytical tools, to better present the information for analytics and visualization. If you want to work in a creative environment where data crunching meets visualization, then learning Tableau is a great option.
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