Measuring how marketing is helping to drive your business is critical. But often marketing’s impact is not widely understood and appreciated.

With Ashish Khandelwal, Mainframe Modernization Engineer at Microsoft, Mukesh Kumar, Principle Group Engineering Architecture Manager at Microsoft, and Tom Griggs, Global Partner Senior Manager at Qlik

Machine learning is used across industries and user communities for a wide variety of predictive analytics needs – use cases ranging from sales forecasting to churn reduction, customer lifetime value, inventory optimization, capital allocation and more.

Qlik’s entry at the Gartner Analytics and BI Bake-Off 2022 looked to address the big questions around clean energy and climate change and found some surprising insights.

“I Wisely Started with a Map” – J.R.R. Tolkien The need for real-time data has never been more crucial, with organizations in every industry accelerating their digital transformation journeys these past few years to address uncertainty and shifting market forces head on.

As virtual selling and digital buying continues to grow, data, insights and timely action are becoming more valuable than ever.

As uncertainty and volatility become the order of the day, buyer behavior and preferences continue to evolve. The continuing global supply chain crisis has resulted in lost sales and market disruptions that have in some cases widely thrown off forecasts.

As data science has taken center stage in a lot of organizations, many are relearning what they’ve already known – that dry, mathematical calculations don’t inspire and don’t stick. It’s the story that matters. In this second of a two-part blog series, we look at some best practices for data storytelling and how Qlik analytics can help.