Data visualization is the visual representation of data in the different format like pictorial or graphical format. It actually abstracts a large amount of data to help people easily understand and make a decision on the data. It drills down insight the data and pulls out the meaningful data. It is basically used in the data analysis arena.It is an art of representing the data in such way that even a non-analyst can understand it very easily. It includes the use of elements like colors, dimensions, labels that can create visual masterpieces.
Why is data visualization important?
Data visualization is a very important factor for an industry because a human can easily understand a large amount of complex data using charts, graphs over spreadsheets. You can do the experiment with data to explore the new scenarios by making the adjustment. It also helps the industry in many ways:
- It easily captures the areas in which data that needs to be improved.
- We can easily understand the customer behavior in particular areas through data.
- It helps you understand which areas need more attention through data.
- It easily forecasts the total sales.
- We can easily take a decision on a large number of data regarding prices, updation.
Data visualization tool
Today the data visualization tools are far better than the spreadsheets in the infographic, geographic maps, bars, charts etc. These things enable the user to manipulate or explore the data for analysis in a better way.
There are many tools for data visualization but one of the best is Tableau.
Data Visualization tools and spreadsheet
There are many tools for data visualization in the market that helps you to create interactive dashboards. Each one of tools has its pros and cons, so when you explore some of them to see what works best for you. My personal preference is Tableau.
What is the reason that someone wants to invest in a tool like a Tableau? I mean you can use Excel to accomplish the same thing instead? From my point of view, Data visualization tools provide more benefits.
The capacity of most data visualization tools far exceeds than Excel, which has 1,048,576 rows by 16,384 columns. But some data visualization tools can have the data as you have the memory to support.
Data visualization tools also provide us endless and instant flexibility. It is in-memory analytic tools. It means that they load the data into your computer’s memory and it will allow you to slice, dice and analyze data in real time. It also needs to be a “read-only,” which means that it doesn’t destroy your actual data. That would be better you know it encourages to experiment because of you no need to worry about destroying your data.
Data visualization tools also provide more data connectivity opportunities than Excel does. A few applications can interface locally to an information source, which can either be CSV/Excel sends out, or guide associations with MySql, Google Analytic and so on as it additionally encourages scalability. You can easily hit a “refresh” button and the data is up to date by using a form of reference links instead of imports. It means that once you have built your report, you will never have to create it again.
Data visualization tools also help you to bring together your data from different channels so you can get a complete picture. It is the key because, in order to drive results in the digital space, you can no longer look at practices in silos. The same goes for your data. It means you can’t really create a strategy in the digital space without combining your channels into one place.
Core Difference between Data visualization tools and Spreadsheet tools
1.) Exploring Data
Organizations remain competitive within their markets with the help of Finding key insights in data. Spreadsheet tools and data visualization tools differ greatly when we talk about the ability to explore data and finding insights.
You must already have an idea of where the data needs to lead you to find critical insights When working with Spreadsheet tools. Because excel saves data in a tabular format, it means you have to do the mapping to get your answer, building formulas and visualizations, and analyzing the information. That is the reason that the process of drilling down into data to be less flexible, and it makes it harder to explore information on a granular level.
On the other hand, data visualization tools allow you to freely explore data without knowing the answer you want ahead of time. You are able to spot correlations and trends with drill-down and data blending features built in, and then dig down to understand what caused them to happen, rather than the other way around.
2.) Automation Functionality
For up-to-date data to make critical decisions many organization depend on this. Spreadsheet tools and data visualization tools can work with static and live data from multiple sources. A spreadsheet tool includes physically programming forms or making macros that consequently update the worksheet’s information when you open the document.
An easy macro can be created with Excel’s Power Pivot and macro recorder tools. When we are creating advanced macros or manipulating existing ones requires Visual Basic Application knowledge. By the way, creating macros can be time-consuming, but reduces the time it takes to complete repetitive tasks in the long run.
When we talk about data visualization tools it is simpler with creating processes and calculations. We can type the formula once and then stored as a field and it can be applied to all rows referencing that source When we are creating calculations in a tabular format. By this process, we can make easier to create and apply recurring processes. Data visualization tools also provide users to create custom formulas.
We first manipulate the data on the cell level, then manually create visualizations like graphs, charts etc in Excel. To simplify visualization creation first we need to deep understanding of how features of excel work.
Data visualization tools visualize data from the start and it allows you to see the consequence right away. Data visualization tools can differentiate correlations using color, size, labels and shapes and give you context as you drill down and explore on a granular level.
You can say data visualization is an art. Data visualization tools are very important for any organization because by this we can take very easy and quick decision on a large amount of data on the basis of graph or pictorial representation. Data visualization tools are very easy that even a non-technical person can understand them easily.