Data Visualization Blog

Making the Gartner Magic Quadrant, part 2: data discovery advantage

Posted by Dan Potter

In my previous post announcing Datawatch’s debut on Gartner’s 2015 Magic Quadrant for Business Intelligence and Analytics, we talked about how our strong scores for customer experience contributed heavily to Datawatch’s ranking. Our data discovery capabilities were also a key factor in making the Magic Quadrant cut. A core function for data discovery solutions is […]

What you need to support big data

Posted by Michael Morrison

Big data comes with a wide variety of concerns, especially in regard to storage and networking. When it comes to choosing a big data analytics package, your decision likely depends on how well its visualizations convey information and whether or not it integrates well with existing architectures.

Is your customer data just sitting there?

Posted by Jon Pilkington

If you have all this data on your customers but don't analyze it, then how can it benefit your business? Think of it this way: Your customer relationship management (CRM) deployment provides you with more information than you know what to do with, so why not make the most out of it?

Datawatch debuts on Gartner’s Magic Quadrant for BI and Analytics

Posted by Dan Potter

We are excited to be positioned on Gartner's 2015 Magic Quadrant for Business Intelligence and Analytics for the first time. We are excited to be positioned on Gartner's 2015 Magic Quadrant for Business Intelligence and Analytics for the first time.

When will data preparation tools come to fruition?

Posted by Jon Pilkington

Before analysis can occur, data must be prepared. At times, some people don't appreciate the sweat that goes into blueprinting and launching a large-scale data analysis project.

Machine learning is great, but how are companies using it?

Posted by Michael Morrison

Machine learning is a growing component of the larger IT industry. Lately, I've been thinking a lot about artificial intelligence - specifically, how machine learning (which is rooted in analytics) is a subset of this technology.

6 big data terms you may have used out of context

Posted by Michael Morrison

It's easy to get lost in the world of big data jargon. When discussing any IT-related topic, it's easy to use terms that are related to certain subjects, but don't actually describe the function or technology you're talking about.

How telecom companies are using big data analytics

Posted by Dan Potter

How are telecommunication companies using real-time analytics? Telecommunications is a pretty hot topic nowadays, especially considering the Net Neutrality debate that has flooded United States news outlets over the past few months.

Utilities taking a comprehensive approach to data analytics

Posted by Michael Morrison

Smart grid analytics are being heavily integrated into utility operations. I've often discussed the energy industry's use of big data to better allocate electricity output from green technologies and enhance smart grid solution functionality.

Incomplete data: What it is, what to do about it

Posted by Jon Pilkington

There may be a wrench in your data collection program that's providing you with incomplete information. Unless you know for sure that your data aggregation systems are providing you with concrete information, there's a chance the "actionable insights" you're hoping to glean are only half-correct, if at all.

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