Importance of Tableau in Data Analytics
Tableau enables businesses to make decisions using the data visualization features available to business users of any background and Industry. It empowers businesses to keep up with the continuously evolving technology and outperform its competition through an innovative means of visualizing their data. There is not a single data source that Tableau fails to connect with. Let it be Data Warehouse, MS Excel or any web data, it establishes a connection with all of them. Basically, in any type of data analytics, Tableau provides an end to end insight by transforming data into visually engaging, interactive views in dashboards. With easy to use drag-and-drop interface one can come up with insights in few moments rather than months or years.
Responding to Competitive Dynamics
Often the difference between winning and losing in today’s marketplace is the ability to respond to ever-changing conditions, anticipating customer behavior or responding to competitive dynamics. Now more than ever organizations need solutions that allow for easy access to the volume and variety of data that can drive and support dynamic decision-making. Competitive pressures and new sources of data are creating new requirements. Tableau data visualization platform simplifies the data analysis and removes unnecessary complications, focuses on what matters most – finding the real value in your data. A simple drag and drop interface in Tableau is easy to learn and eliminates IT staff dependency.
Users are demanding the ability to answer their questions quickly and easily. Tableau is an excellent fit for organizations that do not have large IT departments but are looking for a tool that offers a strong visualization suite and a quick deployment. It enables the users to do their own analysis with simple drag and drop, point and click feature to easy to build charts, reports, dashboards and stories and has an in-memory data engine is not just restricted to fit data into your machine’s RAM.
In-Memory Technology
The in-memory technology makes use of all the memory on your machine, down to the hard disk, so the analysis is amazingly fast at the same time. Several clients are looking to adopt user-friendly BI applications and analytics tools to create KPI-specific dashboards for their power users, functions and leadership. An effective client communication and empowerment could be achieved with Tableau by the usage of BI that enables them to analyze, visualize and communicate information in the most effective way possible.
Assessment Study
The processes will have an assessment study to identify all stakeholders and determine the firm’s readiness and suitability to adopt big data. It will be categorized into Identified business use cases where big data could be a game changer, aligned them to their strategic priorities, illustrated a roadmap for future and clearly defined business benefits, Prioritized and selected a use case for improving the customer revenue based on their past behavior, Definition and implementation of 5 KPIs such as Customer Lifetime Value (CLV), Average Revenue Per User (ARPU), Drop Rate, Retention Rate, Tie Ratio, Value based customer segmentation, Definition of a statistical model to accurately predict the CLV values for a criteria of users by providing a comprehensive solution spanning data extraction from multiple sources, normalization, storage, analysis and visualization using advanced tools and techniques.
Functions and Models
R functions and models can be used in Tableau by creating new calculated fields that dynamically calls the R engine and pass the result values to R. The visualization engine in Tableau utilizes the results returned back and it makes easy to add new data sets, be it an excel workbook, a flat file or any database. Therefore with the implementation of Tableau, multiple ways can be discovered and various ways to uncover insights could be driven enabling the users to make faster and fact-based decisions which will be helpful to increase customer lifetime and revenue.
