With Qlik's new solution, it is possible for the entire company to – simply and without coding – make predictions and plan analytical decisions in their use cases, as well as explore predictive data and test what-if scenarios
Credit: Qlik website
Since its launch, in the last quarter of 2022, a growing number of organizations from different segments have adopted the Qlik AutoML™ to improve decision-making through the power of predictive data analytics, which in 90% of use cases does not require deep expertise from professionals like data scientists.
O machine learning It is used across all industries, but its wider adoption has been limited by a lack of data scientists and resources for this purpose. Qlik AutoML bridges this gap simply and without coding, allowing users and analytics teams to leverage machine learning to train models, make predictions and plan analytic decisions in their use cases, as well as explore predictive data and test scenarios. hypotheticals with Qlik Sense®, which makes it possible to schedule alerts and automations for action across the enterprise.
Organizations such as Chef Works, RevLocal and Bentley Systems are among the names that have adopted Qlik AutoML to better predict turnover, increase efficiency, and attract and retain customers by modeling likely outcomes and dynamic strategies based on predictions.
Another example is Polygon Research, which services the mortgage industry with smart market actions. The brand uses the tool to make forecasts in areas such as loan payments and help creditors take assertive actions, offering options for new financing or changing the terms of a loan.
“This is where AutoML really shines,” says Greg Oliven, CTO of Polygon Research. “It is possible to analyze individual loans, see the percentages of each variable and the cumulative decision: will this loan be paid early or not? What is the forecast? And what is the strength of this forecast?”, he adds.
More value from data
AutoML can be used in many departments of an organization among employees in the areas of sales (forecasting, turnover and retention), marketing (customer value and demand forecasting), finance (risk management and investment optimization), HR ( employee retention, satisfaction and recruitment) and supply chain (forecasting, inventory bottlenecks and transportation optimization) – all areas can benefit from better forecasts that drive proactive engagement.
“Modern analytics, when powered by machine learning, can eliminate assumptions about the future and help decision makers know what is likely to happen, why an outcome is likely, and most importantly, what changes will influence the outcome,” says Josh Good, Vice President of Product Marketing at Qlik. “Qlik AutoML is helping organizations get more value from their data and empowering their teams to look further when making decisions that impact the bottom line.”
