All you need to know about Tableau

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By Inversa Technosoft

What is Tableau?

Tableau is a business intelligence platform that allows companies user to see and understand their data. Dashboards are the core of Tableau, and learning to develop and build effective dashboards is necessary to using the tool and bringing the data to life.
The Gartner Magic Quadrant ranks technology vendors in the business intelligence space, and Tableau has been listed in their leader category continuously for the last 6 years. With an overall rating of 4.3 out of 5, as of today, Tableau is the most reviewed and highest rated data visualization tool.

“I am working as a Report Analyst in a MNC Company and the only tool I use for work in Microsoft Excel. I am cleaning data, making graphs, creating complicated dashboards using micros and its fun”

What is the use and role of Tableau?

Tableau is a very intuitive platform, which can understand data patterns quickly. Once we learn the layout of the tool, we can get started with building and creating dashboards & analytical reports. A dashboard is a graphical summary of various pieces of important information, which is used to give an overview of the business problem. Using Tableau, it doesn’t take long to produce the required reports, and spin up dashboards pretty quickly. We can also generate a lot of flexibility in our reports. Frequently we might create one particular view of the data, but subsequently, explore and dig into the data and discover other findings. In short, Tableau brings data to life through visual analytics.

What is the use and role of Tableau in Data Science?

Data Science is about working with big data. Excel also works with data, but Excel is limited to one million rows, which is typically not viewed as big data. In order to create a visual story, dive into data, change charts or work around things so that we can provide an answer to a given question, we have to be able to explore large databases with ease. This is not possible using Excel, hence the use of Tableau becomes of primary importance.
Finding key insights in data is a primary task of a data scientist, as this helps organizations remain competitive within their markets. The ability to explore data and find insights is where Excel and Tableau differ greatly. When working with Excel, we must already have an idea of what is the business insights we want to see. However, Tableau allows us to freely explore data without knowing beforehand the insights we want to see. With drill-down functions and built-in data blending features, the analyst can spot correlations and trends, and then dig down to understand what caused them to happen, rather than the other way around.
Some of the uses of Tableau in data science are the following:
Segmentation & Cohort Analysis. This breaks down a customer’s contribution to total sales, across product categories.
With calculated fields, we can easily perform arithmetic operations, express conditional logic, perform advanced analysis like Level of Detail (LOD) Expressions and Table Calculations.
Creation of statistical modeling capabilities, including trending and forecasting. We can quickly add a trend line or forecast to any chart, with a simple right-click.