Analytics
News, events, thought leadership and more.
Getting Analytics Unchained requires two key components: faster data processing and analytics that doesn’t require coding. Since most of our predictive analytics capabilities are based on the open source R programming language, a lot of people wonder how it’s possible to build predictive models without having to write code. And then, make them flexible enough so they can scale without fear of the model crashing.
We recently announced a partnership with Revolution Analytics that eliminates these worries and changes the complexity of the market. Now, pre-packaged R-based macros give users the ability to drag and drop predictive analytics procedures directly into a workflow without having to know the coding or programming language behind it. When combined with the processing power of Revolution Analytics, this capability allows users of any skill level to build large-scale predictive models in R without limits.
Many people are discovering the power and flexibility of open source R, but still approach it with caution due to concerns over ease of use and scalability. The capabilities enabled by this partnership with Revolution Analytics will change the way organizations take advantage of predictive analytics. I think Virginia Backaitis summed it up perfectly in a CMSWIRE article when she stated, “This Partnership could present a substantial threat to Analytics and Business Intelligence providers like the SAS Institute among emerging and mid-sized Enterprises.” Thanks for reading.
Analytics Unchained Blog Series
| Part 1 – Remove the Complexity in your Analytics Software Cost |
| Part 2 – Different Analytic Challenges Don’t Require Expensive Software |
| Part 3 – Buy What You Need, Not What They Want to Sell You |
| Part 4 – Analytics Unchained: Teradata and Revolution |
| Part 5 – Pay for the Results, Not for the Luxury |
| Part 6 – R You Ready to Improve Your Analytics |
| Part 7 – Analytics to the Masses |
| Part 8 – Analytics Comparison: Alteryx vs. SAS |
| Part 9 – What is the True Cost of your Analytics Solution |
| Part 10 – Improving your Analytic Outcomes Over SAS |
