34 Data Visualization Tools for Better Business

Humans are naturally visual creatures, so it is no surprise that we search for better ways to portray and understand what data is telling us. Data visualization is one of the most effective ways to achieve this because it enables us to take data or ideas that are abstract and difficult to understand as written, and turn them into something easily understood in a more graphical or visual format. To learn more about data visualization and how organizations use it, see our blog post.

However, for any data visualization to be effective, it requires the right tool – which in many cases can mean a multifunctional tool that includes capacity for both visualization and analysis.

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Improving Understanding with Data Visualizations

As we become better at collecting and analyzing data, we also have to become better at explaining what it all means. Data visualization is the use of algorithms to create images (graphical and pictorial) from data so that humans can more effectively understand and respond to that data. It is important because it enables us to digest large amounts of complex data that would otherwise be overwhelming or difficult to understand.

To better understand data visualization, there are several questions that we will answer:

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Pragmatic Partnership for AI Adoption

We are happy to have interviewed Ben Lamm, serial entrepreneur, co-founder of Conversable and Hypergiant on their pragmatic approach to help enterprises leverage AI and machine learning. You can read more about Ben on his Wikipedia page.

You could possibly be the only one leading 2 AI companies. Can you briefly tell us why you founded Conversable and Hypergiant and the advantages of leading them both?

I noticed that when it comes to AI it’s still very shrouded in darkness and there are a lot of companies selling AI snake oil that has caused serious scar tissue.

Put simply, AI has been over-promised and under-delivered for far too long. It has massive potential to change the way we do business, but not if we bury it in false hope. Read more

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AI talent war: Struggle to attract top AI leaders [2018]

We set out to quantify the efforts of companies to attract top AI leaders and companies.

Company acquisitions

CBInsights prepared this excellent infographic on large tech’s AI company acquisitions:

CBInsights

Personnel acquisitions

Apple hired Google’s head of search and AI

It’s impossible to make a complete list on this topic but feel free to contribute other significant developments on the AI talent war.

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Data Integration Tools: In-depth Guide [2018 edition]

Data integration refers to the processes for taking data from different sources and making it usableThere are four broad subcategories of data integration that each have their own specific tools:

  1. Data warehousing
  2. Data migration
  3. Enterprise Application Integration
  4. Master Data Management

For a more comprehensive look at the topics above, be sure to check out our data integration blog

In this article, you can find out more about these different categories and browse over 40 vendors across them.

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