Systems | Development | Analytics | API | Testing

This quote from Niccolò Machiavelli – an Italian politician, historian, and philosopher from the Renaissance period, has profound relevance to emerging technologies.

There is a common misconception about data-informed decision making. It goes that once we implement the right tools, and figure out how to analyze the data correctly, the data will automatically turn into insights and will translate to better business decisions. It sounds great in theory.

If you could have analytics everywhere, there would be an abundance of insights, which could lead to a boom in decision making on nearly every level, regardless of the situation or user. This is the notion behind the importance of embedded analytics.

Radnor, PA - Qlik®, a leader in data analytics, today announced the acquisition of Podium Data, an enterprise-grade data management company whose solution simplifies and accelerates customers’ ability to manage, prepare and deliver analytics-ready data to every business user across a diverse data landscape. This acquistion expands Qlik’s mission, moving beyond analytics to being a provider of solutions that democratize data for every user to create a more data literate world.

Putting an end to the distribution of useless static reports, the risk inherent in manual spreadsheets and the false hope of inferior dataviz tools is nothing short of a Revolution.

In today’s world of readily available apps, whether on your phone or a cloud service, consumers do not expect a lot of training before starting to use them. Apps are designed to be intuitive and lead you through them in the way that you would expect them to work – as it relates to the purpose of the app. Same is true with analytical applications. The best ones are intuitive – they look familiar and are intuitive to navigate.

The much-anticipated Qlik Sense June 2018 Release has arrived and it includes so many great new features - we would like to highlight just a few…

In my last blog post, I finished up how to create maps with your data using either point, area or flow representation. Today we’re starting with a new topic focusing in on how to visualize the distribution of data. You may remember from my “Mapping data to visualization usage” post that one way to break down the usage of chart is to divide them into these four groups: Comparison, Composition, Distribution and Relationship.

New and Existing Applications Extend Five Year Partnership; Innovations Showcased at UN’s STI Forum 2018

A View from the Big Data & Analytics Retail Summit.