Data Visualization becomes more effective and simpler when done with Tableau, R and Python
At its barest, data visualization is, as the term denotes, visualization of data. This refers to data that is represented not just in text or word format, but in the form of infographics, tables, pictures, charts, diagrams, maps, graphs, etc. As is evident from this simple explanation, data visualization involves the use of these aids to give greater clarity to information (data) and make it easier to interpret.
Data visualization is a set of tools but more importantly, it is a creative means of putting across data that becomes interesting and interactive. Towards giving data this character, data visualizers create aids such as storyboards and dashboards to make data more lively and presentable rather than being in a staid, raw form. In the context of business, it brings in a method or way of understanding data and how to use it for making business decisions.
Yet, the beauty of data visualization is that it need not be restricted to business. Even data from areas seemingly completely unconnected to business can be represented in a wonderfully creative manner using data visualization. Data from areas as varied as history, government, finance, technology, urban planning, astronomy, fashion, demography and many more subjects can be visualized for a very attractive effect.
What makes a career in data visualization valuable in today’s world?
While all the areas in which data visualization are very active in today’s world and are a strong source for data visualization, there is one truly critical factor that has brought data visualization to the fore today. It is data science. Data science is a branch of Big Data that generates lots of data to help in decision-making. The role of data visualization can never be understated in such a data-dependent area as data science.
Big Data and data science have the potential to make an unimaginable impact on our future in many ways. Being able to generate data for almost everything that we can think of, Big Data is set to alter our approach to life in the coming generations.
It is in a data-heavy field such as Big Data or data science that the role of data visualization becomes central. Data in themselves don’t mean much unless there is a method of making sense out of them. This is the core function of data visualization. Data visualization goes beyond just presenting raw data colorfully. The core of data visualization is that it should produce meaningful and critical insights.
It should generate intelligence and should lead to proper decision-making. It should be able to mix the elements of creativity and presentation with statistics and data judiciously and attractively. It should strike the right balance between content and presentation. A superbly visualized presentation could convey little and very powerful data could fall by the wayside due to a pedestrian form of presentation. A data visualizer has to strike the right mix of the worlds of creativity and technology to bring about not just added effect, but sensible intelligence.
Given all the uses to which data visualization can be put, it is natural that it is a profession that is in great demand today. Data visualization is gaining prominence as a very valuable teaching aid in many parts of the world.
Types of data visualization
Data visualizers visualize the data they have with them in three distinct ways:
Abstract data: This involves abstracting internal data that have no spatial elements and creating graphs out of them. Business Analytics is one of the core areas in which internal abstract data is visualized.
Mapping of data: In this method, data visualizers map spatial data to show where the inputs are coming from, where they are going, and what can be done about it to improve the business bottom line. A typical example is online food services, which track data to get an idea of where people are buying from, what they are buying, how much they are spending, what they are looking for and such other parameters. This helps them to analyze data to target their marketing and advertising more effectively.
Storytelling: Data is then presented in the form of stories to make the data more pleasant and interesting. This helps the business to deliver its message and its products to its market segment effectively.
The role of Tableau, R and Python in data visualization
Data visualization becomes possible with the use of a few tools and programming languages. These are Tableau, R and Python. While tableau is used for the visualization part per se by being able to help produce a range of all the inputs needed for data visualization, such as charts, tables, graphs, etc.; R and Python are scripting languages that make its realization possible technically. This makes Tableau, R and Python indispensable to data visualization.
So, when starting a career in data visualization, isn’t it necessary to get a thorough and solid understanding of Tableau, R and Python? Who would want to be foolhardy to venture into a career in a highly developed technical area without the requisite knowledge and skill?
This is where Simpliv is of tremendous help to you in taking up a career in data visualization. This Fremont, CA-based learning platform has designed a course on data visualization which will help you understand the concepts behind using Tableau, R and Python in this field. This course is designed for those who want to make it in a career in data visualization and graduate to a higher level in their profession.
Course schedule
Spread over a period of 45 hours, this virtual classroom course on Data Visualization with Tableau, R and Python will offer complete learning that professionals need to grow in their careers and chart their own career path. This course will be offered over a period of three weeks starting January 21, 2019 and will be held from Monday to Friday, from 7 PM to 10 PM, IST. It will conclude on February 8, 2019.
Benefits of taking up this course
Tableau, R and Python skills constitute the core of data visualization. This course on data visualization with Tableau, R and Python aims to give learners the knowledge of these areas which will help them understand these concepts and build a career in data visualization. With this knowledge, they improve their chances of getting absorbed by the industry. They will understand how to choose a combination of Tableau, R and Python for making Data Visualization effective.
The heart of data visualization is how well its three elements are mixed. This course will give participants a proper idea of how to mix and match these. It will show them how to adapt the right tools for doing so. Participants will be able to understand how and when to use Tableau, R and Python for Data Visualization.
At the end of the learning, participants will earn a certificate from Simpliv. This will help them to gain credibility in the job market. It will be a significant value addition to their CV and will strengthen their prospects in the job market.
This course will put learners on the path to a career in data visualization. The career prospects for such professionals are attractive, considering that data visualization is a relatively very new field of specialization in the IT realm: on average, they earn between $74000 and $75000 or $30 an hour in the US. More than anything else, data visualizers can work in multidisciplinary areas such as data science.
Considering the enormous value that a course of this nature offers, it comes at a surprisingly competitive fee of just?9,999. This special price is only for who enroll for this batch, for whom there is a discount of over 40%. The regular price of this course is?16,665.
Course content
Simpliv has designed this course on data visualization for Tableau, R and Python to help participants gain clarity on the following aspects:
- When to use the right tools
- How to connect to the right data source
- How to connect Tableau Desktop with R to optimize the functions of R
- Packages
- Libraries
- Saved models
- Using Python scripts for fields in Tableau in the same way as is done with R
This course on Data Visualization with Tableau, R and Python offers learning on:
- Visualization with Tableau
- Tableau - An Introduction
- Aggregation and Granularity
- Action Filters and Action Highlights
- Customer Segmentation Dashboard
- Data Blending
- Find top 10 Gems
- Table Calculations (Explaining various Table calculations)
- Difference between Table calculations and Calculated fields
- LOD Functions
- How to connect to databases (Video based)
- How to integrate Tableau with R (Video based)
- Dashboarding Techniques
- Other Charts
Python and R basics
- Tableau - An Introduction
- Core programming concepts
- Objects in Python
- Visualizations in Python
- Packages in Python
- Packages in Python
- Matrix Operations
- Dataframes
- Introduction to R
- Objects in R
- Core programming concepts
- Visualizations in R (Packages in R)
- Matrix Operations
- Dataframes
- Lists in R
- Apply family functions in R
- Projects and Tests.
Simpliv
Email: support@simpliv.com
Phone: 7676008458
Email: sudheer@simpliv.com