In this episode of Making Data Simple we hear insights from IBM Machine Learning Hub data scientists Jorge A. Castañón and Óscar Lara-Yejas as they discuss what machine learning is and is not. They also answer the most controversial question today: Will machines take our jobs? Come find out!
Organizations are collecting terabytes of data, so it’s not surprising that organizations are scrambling to identify a data management solution that fits their unique environment. The freedom of choosing the right data source to fit an organization’s data storage strategy is the key to robust data
How do you provide answers to clients prior to them asking? What do you do with an abundance of client data? In this episode of Making Data Simple, Tracy Bolot, Director of Digital Client Support for Analytics at IBM, talks about how to maximize teamwork and strengths to enrich your clients'
There’s a revolution taking place within information governance. This change is driven by the growing needs of business users, and the recognition that trusted, high-quality, easy-to-find data can be the differentiator that drives better business outcomes.
In a time when data is perhaps a business’s most valuable resource, the ability to access, protect and analyze information plays a critical role in an organization’s overall multi-cloud strategy. Here's how to succeed.
Learn how the IBM Integrated Analytics System, a unified data platform built on the IBM Common SQL Engine, helps do data science faster with high performance, embedded machine learning capabilities and built-in tools for data scientists to deliver analytics critical to increasing your organization’
Protecting personal and sensitive data is vital. But, understanding the regulatory environment and available tools is just the first step. There are still challenges when building and managing test data environments. Here's how to overcome them.
In this first episode of Making Data Simple, we welcome Daniel Hernandez, VP of IBM Analytics Offering Management, who helps us navigate "the big data problem" and shares why he doesn't like the term "big data."
There’s no doubt data science and machine learning are main areas of focus for enterprises to better their business. However, talking about data science and machine learning isn’t the same as making it a reality.
Some people think of master data management (MDM) purely as a platform for organizing and mobilizing enterprise information. While this is true, leading companies view MDM more as a philosophy or a set of best practices, not just a suite of software tools.