Tag: Predictive Analytics

Birst Smart Analytics: Using AI to Operationalize BI

How do you deliver more insights out to more people? Operationalizing BI and analytics – that is, putting the power of data in the hands of everyone across the enterprise, not just analysts and data scientists – has always been the mantra for Birst co-founder Brad Peters.

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How AI is Lowering the Barrier to Entry for BI and Analytics

According to Gartner, more than 3,000 CIOs ranked Business Intelligence (BI) and Analytics as the top differentiating technology for their organizations. If BI and Analytics is such a game-changer, then why is the average adoption rate in organizations only 32%? Despite the efforts of Cloud BI vendors making it easier for users to acquire, explore, and analyze data sources without IT dependency, lack of data literacy and analytic skills still hinder widespread adoption for data-driven decision making.  But the industry is undergoing a fundamental transformation. The mainstream arrival of Artificial Intelligence (AI) brings with it the potential to finally meet the demand for actionable, enterprise-wide, fact-based decision making.

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Seven Steps to Success for Predictive Analytics in Financial Services

Remember when you began your career and the prospect of retirement was an event in the distant future? How many of the poor decisions you made over the years could have made for a better retirement outcome had you had a crystal ball to see into the future? With better knowledge about the future, would your decisions have been different?

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What AI Means to a Data Scientist

How many times have you wished for more hours in the day so you can complete more tasks? A key goal of AI or machine learning automation is to have machines complete tasks for you, freeing up time so you can focus on the more complex, higher-value tasks. However, there are simply not enough data scientists in the world to deliver on the AI potential. Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases?

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Reading the Data Tea Leaves – Can HR Help Predict Future Business Success?

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HR predictive analytics is attracting a lot of attention. Last year, Towers Watson found that one in three organisations planned to increase spend on their HR function by more than 20 percent, and HR data and analytics tools rated as one of the top areas for investment. However, just looking at HR data in isolation does not represent the best opportunity to make an impact.

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Influencing Outcomes: Prescriptive Analytics for Daily Users

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As the awareness around the possible gains that can be afforded to organizations by leveraging analytics and business analytics tools grows, so does the awareness of the various categories of analytics. When you look at the Fortune 1000, I would estimate that 75 percent of all large corporations are familiar with “prescriptive analytics.” These enterprises have IT teams that know prescriptive analytics exists and they understand the benefits this approach offers. However, I would also say less than 25 percent are using prescriptive analytics at scale.

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