Blogs

Fast track your data

Fast track your data

May 25, 2017 | by Oliver Clark, Social Media Execution Strategist, IBM
Join our CrowdChat about developing a competitive advantage with machine learning, data governance and data science.
What is optimization and how it improves planning outcomes

What is optimization and how it improves planning outcomes

May 16, 2017 | by Ryan Arbow, Product Manager, Advanced Analytics, IBM
This is the first in a sequence of blogs that looks at how Planning Analytics and Decision Optimization can help organizations go from a plan to the right plan by leveraging optimization throughout the planning process.
Sparking change: How analytics is helping global communities improve water security

Sparking change: How analytics is helping global communities improve water security

May 11, 2017 | by Andrea Braida, Portfolio Marketing Manager, IBM
Most of us are privileged enough to live in societies where clean water is a given. When our physicians and the media advise us to stay hydrated, it’s a simple health consideration. But in many countries, access to water is a huge issue – approximately one third of the world’s population does not...
Top 3 ways to measure the success of your analytics investment

Top 3 ways to measure the success of your analytics investment

May 9, 2017 | by Susara van den Heever, Product Manager – IBM Decision Optimization, IBM
Line-of-business (LoB) stakeholders want to know that their analytics investment will help them make better, faster, and smarter decisions, with measurable business results. But for many, measuring success from applying Machine Learning and Decision Optimization is not obvious. Learn the top 3...
Analytics and the cloud: The rise of open source

Analytics and the cloud: The rise of open source

May 9, 2017 | by Steven Lockwood, Executive Information Architect, IBM
This is the fourth in a series of blogs on analytics and the cloud. Read our introduction to the series. This blog concerns itself with the rise of open source software and how it is used for a whole host of analytical purposes. However, as will be seen in this blog, there are significant gaps in...
The Quant Crunch: The demand for data science skills

The Quant Crunch: The demand for data science skills

May 1, 2017 | by Steven Miller, Data Maestro, Global Leader Academic Programs, IBM Analytics Group, IBM
Extreme focus has been placed on the nascent data scientist role but, in contrast, the much larger demand for data-savvy managers (1.5 million new positions) has largely been ignored by academia.
Real-time personalization with streaming analytics

Real-time personalization with streaming analytics

April 27, 2017 | by Preetam Kumar, Product Marketing Manager, IBM Analytics, IBM
Context-aware stream computing helps you become more responsive to emerging opportunities. By using innovative technologies to understand the context of data and analyze data in real time, you can put data to work.
Big Replicate: A big insurance policy for your big data

Big Replicate: A big insurance policy for your big data

April 18, 2017 | by Andrea Braida, Portfolio Marketing Manager, IBM
Dwaine Snow is a Global Big Data and Data Science Technical Sales Manager at IBM. He has worked for IBM for more than 20 years, focusing on relational databases, data warehousing, and the new world of big data analytics. He has written eight books and numerous articles on database management, and...
What to do with all that machine learning data

What to do with all that machine learning data

April 18, 2017 | by Susara van den Heever, Product Manager – IBM Decision Optimization, IBM
Many businesses are starting to notice that without converting the masses of new data generated by the Machine Learning (ML) wave to Smarter Decisions, the impact falls short of expectations.
Analytics and the cloud: NoSQL databases

Analytics and the cloud: NoSQL databases

Schemaless databases and the role they play

April 6, 2017 | by Steven Lockwood, Executive Information Architect, IBM
Although NoSQL database technology has been around for a long time (before SQL actually), not until the advent of Web 2.0, when companies such as Google and Amazon began using the technology, did NoSQL’s popularity really take off. Market Research Media forecasts NoSQL Market to be $3.4 Billion by...

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