Big Data

What data scientists can do with better machine learning

Share this post:

data science machine learningSmart 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.
  • Ask a data scientist: A one-on-one experience. Data specialists from the Machine Learning Hub in Germany will be on-hand to tackle problems, answer questions and share best practices.
  • Mixing oil and water: Getting data scientists and business analysts to work together painlessly. This session will explore ways to help improve collaboration and speed data insights beyond the analytics organization.  

Data scientists are building the data-driven future of business. Machine learning will help them do it. I look forward to sharing ideas and best practices at Fast Track Your Data – Live from Munich. If you can’t make it in person, I hope you’ll join us at the conference through the live stream.

In the meantime, explore more about the IBM data science platform and machine learning.

A version of this article was originally published on the IBM Big Data and Analytics Hub.

More Big Data stories

Global Omnium provides water to citizens at lower cost

Everyone relies on fresh, clean water to drink, wash and cook. However, many people take their water supply for granted, and certainly don’t think about the long journey necessary to convert rainfall from far away into safe drinking water piped into homes. Global Omnium, a large water provider based in Spain, aimed to deliver a […]

Continue reading

Feeding the planet as the climate changes with rapid analytics on IBM Cloud

The latest climate research indicates that the planet might be warming at an even faster rate than previously thought. As extreme weather events such as droughts become more common, it’s becoming more difficult and costly for farmers to irrigate their fields, making crop failures more likely. The current world population of 7.3 billion is expected […]

Continue reading

Data management and Kubernetes come together in IBM Cloud Private for Data

In addition to the short-term benefits of IBM Cloud Private for Data — a data management platform built on Kubernetes with support for Db2, MongoDB and Postgres databases — General Manager for IBM Analytics pointed to the long-term effects in an article at Container Journal this week. As IT organizations continue to take advantage of […]

Continue reading