Data visualization tools for mac os x


  1. Data in. Brilliance Out.
  2. 22 Free Tools for Data Visualization and Analysis
  3. Powerful omnibus software that takes some getting used to
  4. Take the hard work out of creating charts and infographics with these tools.
  5. 22 free tools for data visualization and analysis | Computerworld

It is particularly well suited to handling the huge and very fast-changing datasets which are used in Big Data operations, including artificial intelligence and machine learning applications, thanks to integration with a large number of advanced database solutions including Hadoop, Amazon AWS, My SQL, SAP and Teradata. Extensive research and testing has gone into enabling Tableau to create graphics and visualizations as efficiently as possible, and to make them easy for humans to understand.

The vendor has over 40, customer accounts across over countries, and those that use it frequently cite its highly customizable setup and wide feature range as a key advantage. This however can mean that it takes more time to get to grips with and use it to its full potential. In addition to its data visualization capabilities Qlikview offers powerful business intelligence, analytics and enterprise reporting capabilities and I particularly like the clean and clutter-free user interface.

Qlikview is commonly used alongside its sister package, Qliksense, which handles data exploration and discovery. There is also a strong community and there are plenty of third-party resources available online to help new users understand how to integrate it in their projects. This is a very widely-used, JavaScript-based charting and visualization package that has established itself as one of the leaders in the paid-for market.

It can produce 90 different chart types and integrates with a large number of platforms and frameworks giving a great deal of flexibility.

Data in. Brilliance Out.

Like FusionCharts this also requires a licence for commercial use, although it can be used freely as a trial, non-commercial or for personal use. A key to its success has been its focus on cross-browser support, meaning anyone can view and run its interactive visualizations, which is not always true with newer platforms. Datawrapper is increasingly becoming a popular choice, particularly among media organizations which frequently use it to create charts and present statistics. It has a simple, clear interface that makes it very easy to upload csv data and create straightforward charts, and also maps, that can quickly be embedded into reports.

Plotly enables more complex and sophisticated visualizations, thanks to its integration with analytics-oriented programming languages such as Python, R and Matlab.

22 Free Tools for Data Visualization and Analysis

But it's well-known because it's super lightweight only 33 KB , and it's aces for building not just maps but interactive mapping visuals aimed specifically for mobile devices. That can be a tall order even for some of the commercial BI tools we've reviewed.

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So, if you're not scared of the command line or making an application programming interface API call, then check it out. Backed by Berlin, Germany-based company Datawrapper GmbH, Datawrapper is nevertheless multinational, having been built by a team of designers, developers, and journalists from a number of European countries as well as the United States. The tool is specifically built for journalists looking to create fast, easily digestible visualizations to accompany their articles; however, it's useful for anyone requiring similiar data views.

Powerful omnibus software that takes some getting used to

While there is a paid version that supports the company, there's also a free plan that tops out at 10, charts, which should keep many SMB operators happy for quite some time. The tool is entirely web-based, and the website includes not only access mechanics but also an Academy area in which you can take online learning classes on how to use Datawrapper.

There's a Gallery area, too, called the River , in which users can upload data and their visualizations for sharing. This is a well-known chart-creation tool that was made publicly available by financial news website Quartz in Quartz had developed the tool in-house so its journalists could quickly render numerical data visually to make their stories stand out. Ironically, Chartbuilder isn't very pretty itself and also is not the easiest tool for rank beginners to use.

You'll need to understand how to download the tool and activate a Python script to get it running. But after that, it's simply a matter of cutting and pasting data into the tool also not pretty but very easy , and then generating a graphic that you can tweak via the tool or via style sheets. The only downside to the tool aside from a little upfront complexity is that it doesn't generate interactive visualizations like most of the other tools on this list do. Chartbuilder creates only static charts, though these are very polished, as befits something intended to go from numbers to slick published content in just a few steps.

Information is Beautiful. This is simply a growing library of striking, prebuilt visualizations that other people have created by using a variety of tools. The gallery is fun and everything is downloadable, though you'll need to pay attention to the licensing agreements. These agreements give free access to individuals especially students and academics but, if you're looking to use these visualizations for commercial work, then you'll need to fork over some dough.

Take the hard work out of creating charts and infographics with these tools.

Exactly how much depends on who you are and on an email exchange with the website's owner. Just to warn you: We had asked to pay for a visualization for this story, and two weeks after the request, we still hadn't heard back. So, if fast turnaround is part of your agenda, then look elsewhere.

Open Refine. There's an oft-overlooked underpinning to a successful data visualization: data transformation.

That's especially true today when big data is trying to provide insights across different data sources, maybe a spreadsheet, maybe a long transaction log gleaned from a machine learning ML algorithm. Transforming data generally refers to the painful for normal people process of taking a whole bunch of disparate numbers and turning them into a sleek set of relatable data. That means cleaning data formatting and error checking , transforming it changing from one format such as native Microsoft Excel to another, such as XML , and then making it available to external services such as webpages and those BI tools you're using.

If you're thinking this can be a painstaking, eye-watering, brain-bending task, then you'd be right…unless you use a data transformation tool such as Open Refine.

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This tool began life under Google's flag but was rebranded to stand on its own. It's still both free and easy to use so, if you're banging your head against a mountain of mismatched data, then check it out.

22 free tools for data visualization and analysis | Computerworld

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