Showing posts with label data visualizations tools. Show all posts
Showing posts with label data visualizations tools. Show all posts

Tuesday, August 31, 2021

Big Data Visualization: Tools and Challenges

 Media theorist John Berger believes that people think in pictures. For him, seeing comes before words. He states:

“Unless our words, concepts, ideas are hooked onto an image, they will go in one ear, sail through the brain, and go out the other ear. Words are processed by our short-term memory where we can only retain about 7 bits of information (plus or minus 2). This is why, by the way, we have 7-digit phone numbers. Images, on the other hand, go directly into long-term memory where they are indelibly etched.”

Big data visualization is a technique based on visual elements like charts, graphs, and maps that represent complex concepts and data in a way they become easier to analyze and decipher. The method adds value to your data by removing the noise from data and highlighting the useful information (like trends, outliers, and patterns).

If you’ve ever stared at a massive spreadsheet of data and couldn’t find a meaningful pattern, you know how much more effective a visualization can be.

In the world of big data, it is important to analyze massive amounts of information and make data-driven decisions.

This is where data visualization tools and technologies come into play.

Big data visualization is the key tool to make sense of the trillions of rows of data that you generate every day.

However, not all data visualization techniques prove to be effective.

Not all of them can help tell stories. Traditional elements like plain graphs could be too monotonous to make a powerful point.

So, what is effective data visualization then?

It is a delicate balancing act between form and function.

Combining data and visuals is no less than an art. If you want great analysis combined with great storytelling, your data and visuals need to work together.


How big data visualization works

There are studies by psychologist Albert Mehrabian that indicate that language is decoded on a linear level, while visuals are deciphered on a simultaneous level.

This means that an image can be analyzed instantly, while language requires time to analyze. Data visualization is the technique that cuts-to-the-chase, allowing faster analysis of critical information.

Data visualization solutions help companies spot trends and patterns, and track business performance and goal achievements.

Plain graphs are only the tip of the iceberg.

There’s a whole selection of big data visualization methods that help present data in interesting ways. It is important that you combine the right visualization method with the right set of information.

Big data visualization works by enabling and empowering decision makers at every level of your organization to see and analyze unstructured or unorganized data presented visually with the help of several figurative approaches and methods.

Data visualization allows handling tons of data by converting it into meaningful visuals using widgets and elements. For this, the best software tools are used to operate various types of data sources.

From politicians to sports’ enthusiasts, journalists, engineers and accountants, the application of data visualization is evident in our modern world.

Some of the data visualization techniques used to put together information in a visual way include infographics, heat maps, scatter plots, fever charts, connectivity charts, timelines, treemaps, histograms, and area charts, among others. The choice of technique should depend on the type of data being modeled and the intended purpose.

Big data visualization tools

Big Data is not a new concept. It has existed for decades. It’s just the size of the data that’s new today.

Can you guess the amount of data we’ve generated in just the last 2 years from different sources like mobile devices, computers, and other web connected devices?

It’s a zetabyte of data!

It technically means that every 2 years, we create as much data as we did from the beginning of time or at least 90% of all the data in existence till today.

That’s a lot of data!

Let’s say you are a proud owner of a diamond mine, but you can’t harness the diamonds from that mine.

Is there a point in being the owner? No, right?

It’s the same with big data.

There is no point in collecting large chunks of data if you fail to grasp the information and insights lying beneath it. Data visualization tools help resolve this issue by showing us valuable hidden insights of the collected data.

Some popular big data visualization tools that will help you make the best visuals of your data in the most time-efficient manner:

Tableau

An end-to-end big data visualization tool that enables you to prepare, analyze, collaborate, and share your big data insights. The platform excels in self-service visual analysis. It helps data-driven companies to see and understand their data, create workbooks, visualizations, dashboards and stories.

QlikView

This self-service BI (Business Intelligence) or data visualization tool enables you to work adeptly on the tool without relying on your IT department, with little to no professional expertise. The data security provision of the tool is stringent in the sense that it guarantees the safety of critical corporate data.

PowerBI

This cloud-based big data visualization tool requires no capital expenditure or infrastructure support regardless of how big your business is. It integrates easily with your existing business environment, giving you exceptional analytics and reporting capabilities. Moreover, Power BI ensures that your data is quickly retrievable by removing memory and speed constraints.

Spotfire

This is probably the most complete big data visualization solution on the market that enables you to uncover and visualize new discoveries in your data through immersive dashboards and advanced analytics. Its analytics capabilities include predictive analytics, geolocation analytics, and streaming analytics. The tool’s rich API capabilities let you analyze all the data needed for the most powerful insights.

D3js

D3js is the big data visualization tool that brings your data to life using HTML, SVG and CSS. It combines powerful visualization components and a data-driven approach to DOM manipulation. The JS framework and functional style that it has allows you to make it as powerful as you want to make it.

HighCharts

This insights platform lets you create customized dashboards with different widgets. With this big data visualization tool, you can easily create an interactive chart that uses the data from the HTML tables and presents it more appealingly. HighCharts solely run on native browser technologies and there are no plugins required. It won’t be an exaggeration to say that they are the future of data representation in an approachable way.

Conclusion

By now, you’d know that we are hard-wired to find emotional cues within visuals rather than text.

Data visualized properly leads to information and knowledge. Visualized data has more value because it has been transformed into information. On consuming this information, it becomes knowledge.

“Identifying patterns, anticipating outcomes and proactively optimizing a response will be the basis for competition in the future. In the next 10 years, the companies that don’t have analytics deeply embedded in their business model will most likely cease to exist.” — Gartner

Your business data can communicate critical insights if it’s visualized the right way.

Jellyfish Technologies will help you reimagine your unstructured or unorganized business data on interactive dashboards easily with interactive data visualization services.

Wednesday, May 19, 2021

Power BI Vs Tableau: Comparison Of The Top Data Visualization Tools

 Do you know that trillions of rows of data are generated every day? Curating it or making sense of it is not an easy task. You may have a hatful of data but if it cannot be visualized, there’s no value to it. It is pointless.

But why is that?

Well, because our eyes are drawn to visual elements. Colors and patterns and maps and graphs grab our interest, not massive spreadsheets of data.

Data visualization is the technique that is used to visualize massive spreadsheets of data and find meaningful trends or patterns. It is an integral part of data analysis.

Introduction

Businesses collect a great deal of information through data analysis today. Painting a picture of that massive data is important for the human mind to interpret it in a meaningful way. This is what data visualization does.

Dozens of data visualization tools and techniques that exist today. Some of the most popular data visualization tools include Tableau, Microsoft Power BI, Sisense, Zoho Analytics, IBM Cognos Analytics, and Qlik Sense, among others.

This post compares the two most popular data visualization tools viz. Tableau and Power BI on various parameters.


Let’s get started.

Power BI vs Tableau: Major Differences

Price

Power BI:
Compared to Tableau, Power BI sits at a lower price point. It offers 3 subscription tiers viz. Desktop, Pro, and Premium.

The Desktop version is free and is targeted at individual users. The Pro version is a monthly subscription which starts at $9.99 per user. The scalable premium version is also a monthly subscription which starts at $4,995 per dedicated cloud compute and storage resource.

Being a Microsoft product, this data visualization tool is well set up with the Microsoft ecosystem which makes it pretty affordable, especially for companies who deeply invest in Microsoft software.

For users who wish to test the platform before making a purchase, it offers a 60 days long free trial.

Tableau:
Tableau’s pricing, on the other hand, is more tailored. The popular data visualization tool has moved from bulk purchase models to subscription pricing models recently. Tableau’s subscription plans viz. Creator, Explorer, and Viewer are tailored to specific user needs.

If you wish to test it before making a purchase, the platform offers a 14-day free trial too.

Bottom line
Power BI is generally a more affordable data visualization tool as it sits at a lower price point than Tableau. If you prioritize free trial capabilities, it offers a robust 60-day Pro trial, while Tableau’s free trial is only for 14 days. Additionally, Power BI starts at $9.99 per user per month, while Tableau Explorer starts at $35.

Dashboards

Power BI:
Power BI has real-time data access and some pretty handy drag and drop features that are suitable for even the most novice users who do not have a lot of prior knowledge in data visualization tools. The platform is quite user-friendly which makes it more preferable to users than the Tableau dashboard.

Tableau:
Like Power BI, Tableau’s features are robust too. Compared to Power BI, it is a bit difficult to use. It has an intelligent user interface with a drag and drop table view but some of its hidden features make it less intuitive than Power BI. Yet, the robust data visualization tool proves to be one of the best for data analysts who are familiar with data sets.

Bottom line
While Power BI concentrates more on reporting and predictive modeling, Tableau focuses on live query capabilities and extracts. The user experience provided in the Tableau dashboard is somewhat cluttered, yet it is fairly easy to use as long as you’re comfortable working with data sets. For a simpler user interface, Power BI would be an appropriate choice. Also, if you’re looking for live data access where your teams can react instantly to business changes, Power BI is an ideal choice for you.

Setup

Power BI:
Power BI allows you to build and publish visualizations in 3 forms viz. Desktop, Mobile, and Service that you can choose depending on your role and needs.

The most basic Power BI set up is an Azure tenant that you connect to your Power BI through an Office365 Admin interface. This might seem daunting unless you already have the framework in place to get up and running quickly. The data visualization tool allows you to seamlessly connect existing spreadsheets, data sources, and apps via built-in connections and APIs.

Setting up this platform is pretty simple and usually starts with choosing the version you want to use from Power BI Desktop, Power BI Pro, and Power BI Premium. After making the choice, you upload the data, start exploring your datasets, and bingo! You can start generating your first report.

Tableau:
Tableau installation, on the other hand, requires you to have a computer that satisfies the hardware requirements. If your computer satisfies the minimum hardware requirements, you will get an informational message and if it does not, you can go for a trial installation of Tableau. But, the trial version is not adequate for a production environment.

Bottom line
Setting up Power BI is a lot more simple and less complex when compared to Tableau. If you do not want to worry about the hardware compatibility aspect, Power BI is your ideal choice. However, Tableau is a better option if collaboration is important for you.

If you’ve built your visualizations in Tableau Desktop, you can share them with your team via Tableau Server or Tableau Online, which makes it a highly collaborative data visualization tool.

Summary

It wouldn’t be wise to conclude which of the two is better since they both have their pros and cons, though there are certain functionality gaps between both.

While Microsoft Power BI could prove to be a great choice for your small business, Tableau would work better for your large organization by allowing you to combine large quantities of data points from various data sources.

Your final choice must take into consideration the size and data requirements of your organization.