IBM Data Science
The New Data Science Experience with AI – Infusing Data Science & AI into your business
IBM Data Science, and why does it matter?
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Learn How we are Helping our Customers address Business Challenges with IBM Data Science Solutions
Why IBM Data Science Matters today
With the volume and variety of social, mobile and device data, along with new technologies and tools, data science (03:43) today plays a broader role than ever before. Business considers data science and AI (06:13) to be a technology-enabled strategy. In order for data science to be effective, its full lifecycle not only must support traditional analytics, but it must also work in concert with modern applications. This means that the data science practice must evolve beyond routine, tedious tasks — as much 85% of a data scientist’s time is spent cleaning, shaping and moving data from place to place, often to feed machine learning. That leaves only a small percentage of time to find patterns and trends, to build models, to predict and forecast, and to interpret results.
Fortunately, there is relief. The latest development in modern data science is an AutoAI capability that automates the data preparation and modeling stages of the data science lifecycle. Now, not only can more data scientists use their specialized skills the way they were intended; but more businesses can benefit from data science, from prediction to optimization.
Some of the Key Questions Data Science Will help you to Solve
- Which next thousand customers will we lose and why?
- Where should we set up another kiosk or a new store?
- Which high-performing employees are we at greatest risk of losing?
- If we price products differently, will we save costs?
- Is my team offering the right things to the right people?