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'
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’
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."
Data already is the new currency and is at the heart of everything digital. I like to repeat the adage, “Data becomes Information, becomes Knowledge, becomes Wisdom”. And “It’s all about the data”. So why do we send up probes, sensors or satellites — for the data?
On June 13th 2017, Hortonworks and IBM announced an extension of our partnership. A key part of this partnership is the collaboration on IBM Data Science Experience (DSX). This collaboration is win-win in that it brings a production-ready full-cycle data science experience to Hortonworks Data
The latest executive report published by IBM Institute for Business Value puts the estimated cost of cyber crime to the global economy in a range of USD 375–575 billion per year. Reputational damage, which is hard to calculate, comes on top of all this. No industry and geography has remained
Data is a potent business resource and the key to gaining and maintaining competitive advantage. Last month, IBM and Hortonworks announced a partnership to bring data science to the world on an open platform, offering Hortonworks Data Platform (HDP) along with IBM Data Science Experience (DSX) and
Perhaps one the single most significant changes to the analytics landscape in recent years had been the emergence of the data scientist. This role is continuing to evolve, with many organizations still in the process of establishing how best to incorporate this relatively new discipline into their
Many of today’s top business performers successfully leverage a discipline – data science. Machine learning is one major way to apply data science and with machine learning, the more data we feed in, the better it performs. However, much of the world’s value data cannot be found on the Internet. It
In any successful modern organization, analytics is likely to play a central role in helping decision-makers design and execute effective business strategies. At IBM, as we work with clients across the globe, we’re seeing ever-increasing levels of maturity and confidence in data-driven business
The data lake can be considered the consolidation point for all of the data which is of value for use across different aspects of the enterprise. There is a significant range of the different types of potential data repositories that are likely to be part of a typical data lake.