Turning Data Into Meaningful and Actionable Insights With Tableau

Tableau is a visualization tool that enables users such as marketers, business leaders, managers, statisticians, and financial analysts to present data visually, compelling ways to solve problems and inspire others to make the most out of their data.

Moreover, Tableau also entails visual analytics, which comprises data analytics and visualizations used to synthesize and analyze data by bridging visual representations and analytical processes decision-makers to facilitate data-driven decision-making thinking, and reasoning to acquire an insight to solve complex problems effectively.

In Tableau, data can be analyzed by exploring or asking questions. Tableau quickens the process of analyzing data collected and stored and turning it into visual, interactive graphs and meaningful information that is easier for the user and audience to comprehend.  

Tableau Basics

Loading Data:
Loading data into Tableau is a reasonably simple task.  Data is uploaded by connecting to a local file or server without programming codes or language. Users can link data from various databases and sources such as Excel, flat files, text files, Enterprise Resource Planning (ERP) systems, and servers such as Oracle, SAP, Salesforce, and MySQL. 

Formulating Joins and Calculations:
Joins combine data from different tables, sources, or places, depending on the type of analysis needed and the data structure. Establishing joins of tables with data stored on the same database improves performance by reducing the time it takes to perform data queries.

Calculations are used in Tableau to manipulate data in several ways by creating calculated fields which allow users to create new data from existing data located in the data source. Calculated fields can filter data results, convert the data type of field, calculate ratios, segment data, and aggregate data.

Constructing Hierarchies:
Hierarchies help organize and arrange data fields or attributes in a data set at different levels. Tableau automatically creates hierarchies by detecting significant fields and also allows users to create custom hierarchies. Users can drill up or down the hierarchy to explore and analyze a detailed view of the various hierarchy data levels in once a field is added to the visualization.   

Building Charts:
Tableau enables users to build charts quickly and effortlessly. Charts are created by incorporating fields dragged from the table section and developing worksheets consisting of various features such as rows, columns, filters, marks, and pages.

Creating a Story:
A story in Tableau utilizes an arrangement of visualizations that convey information to the audience. It offers context, a data narrative, and reveals new findings and how decisions are relative to outcomes. Stories also allow users to inquire about the data by asking further questions. Stories turn complex data into appealing, relevant, and purposeful information that is simple and easy to understand.

Visual analytics with Tableau aids businesses to improve their data analysis, understand their data faster, increase their business performance, and improve their decision-making process. For instance, in 2007, Lenovo, a multinational technology company, began using Excel for their data analytics and experienced a long, exhausting, labor extensive, and time-consuming work productivity for several years. At the time, Lenovo generated reports utilizing Excel, which entailed an analytics team that worked approximately seven hours to develop one weekly report. Furthermore, a group of roughly ten associates implemented the Excel-generated reports across Lenovo’s regions and divisions.  

In 2014, Lenovo evolved and adopted its data analytics with Tableau, which entailed approximately 100 users. Lenovo’s team enjoyed time-saving benefits from the ability to create and deliver reports on a daily or hourly basis and faster. For example, Lenovo’s team performed further data analyses and gained insights from their data. Tableau became a vital tool in Lenovo’s business operations. Lenovo shifted its focus and business approach and growth strategies to be more data-driven and data-centric. Lenovo also launched Tableau in India to manage and analyze its data to help with its decision-making process.

Lenovo’s BI Analytics and Visualization team in India further developed Lenovo’s use of Tableau by creating a Tableau sales dashboard for its departments to conduct reporting and ad-hoc analysis. Lenovo grew its operations with approximately 55,000 employees and over 10,000 users with access to Tableau dashboards, a collection of views that allows users to compare an array of data simultaneously.  Tableau contributed to Lenovo’s increase in efficiency by 95% and nearly 3,000 users in roughly 28 countries.    

Tableau is a vital and resourceful tool that incorporates data visualization and visual analytics, enabling users to convey significant points and leverage data visually and effectively, process queries, complete tasks, and develop insights by creating data visuals such as charts, graphs, scatter plots, and maps.  Tableau enables businesses to have more time to focus on the true hidden meaning behind their data, key business metrics and extract valuable insights to assist them in making quality decisions quickly and efficiently to achieve growth and optimize results.

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