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What data scientists can do with better machine learning
Smart companies are finding new ways to squeeze more value out of their massive data storehouses. They’re unlocking insights from their data that build new business models, improve customer experiences and outpace competitors. So where do these business-changing insights come from?
Data doesn’t interpret itself. A table of numbers won’t arrange themselves in a pattern that spells out “here’s what your customers really want.” We look to data scientists to find meaning and value—and those insights can fuel transformation across your business.
Data science itself is undergoing rapid transformation. Early this year, Gartner predicted that nearly half of data science tasks will be automated by 2020.
That’s not alarming. In my view, machine learning won’t just automate data science, it will more profoundly transform and accelerate the businesses that embrace it.
Better machine learning doesn’t replace what data scientists do. But machine learning is building better tools to help them automate processes like discovery and visualization. There’s a huge opportunity for automation to improve the tools that will bring data and data-driven insights outside of analytics organizations. When business users can access and interpret data more effectively, data scientists can focus on more complex data analysis.
It’s no secret that IBM is invested in elevating data science. Year after year, analysts consistently rank IBM as a leader in the data science platform space. We want to give data scientists a platform to share successes and be partners in identifying and overcoming roadblocks.
I hope you’ll join us at Fast Track Your Data – Live from Munich starting June 22, where data science and the impact of machine learning are a core topic. Join IBM and industry leaders for demos, breakout sessions and panels. Highlights include:
- Demo: immersive insights from 3-D visualization for the data scientist. IBM data professionals will show how to bring the power of data science tools to Augmented Reality (AR) visualizations helping to improve user experience, data exploration and analysis.
- Build smarter apps with data science and app developers. This session will explore collaboration and integration opportunities to connect processes that can fuel business decisions….
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