It’s been one year since we launched IBM Cloud Pak for Data (previously IBM Cloud Private for Data), IBM's data and AI platform for today's modern enterprise. Since then, this platform has been embraced by hundreds of customers, and Forrester ranked it No. 1 in their “Enterprise Insights Platform”
On this episode of Data Decoded, host William McKnight sits down with Rob Harris (IBM, chief data governance architect) to discuss the current state of Master Data Management (MDM). They explore MDM's many applications to industries that include healthcare and even consumer products like smart
Imagine a searchable data management system that would enable you to review crowdsourced, categorized and classified data. Consider that this system would apply to all types of data — structured and unstructured — and become more robust as more users analyze it.
Advances such as blockchain technology are steadily gaining traction both in terms of investment and adoption. Well-informed IT professionals are starting to deploy these new technologies to establish a more connected, knowledgeable and secure business. Here are some ways blockchain technology and
How will technology and society change in the next 50 years? On our last podcast, we discussed how technology has evolved in the last 50 years. On our latest episode we look forward to the next 50 years. 2068 may seem far away. But futurists like Rajeev Saxena, IBM Watson amd Cloud Platform Program
Floppy disks, punch cards and BASIC — we’re taking a trip down tech memory lane. How has technology, specifically in terms of data management, evolved in the past few decades? On the latest episode of Data Decoded, Andy Leonard, founder and chief data engineer at Enterprise Data & Analytics,
In this special podcast, our Making Data Simple Podcast host Al Martin is joined by Caleb Curry, data guru for IBM Hybrid Cloud, and Sam Lightstone, IBM fellow of analytics, to talk about their session at the IBM Think 2018 Conference: "Next-Generation Data Management: Power and Simplicity to the
While the proliferation of data will be readily apparent, deciding what to do in response will be less straightforward. The majority of workloads currently sit in traditional, on-premises environments but we’ll see many of them move to private and public clouds over the next over the next five
Data management is a discipline that's remained relatively unchanged and, to put it bluntly, somewhat stagnant over the past 10 or 20 years. Since the dawn of the Internet of Things (IoT), these trends have already reversed.
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
Big data isn’t just getting bigger. It’s getting more valuable. As companies work to unlock more value from their data, one of the biggest challenges to address is disconnected data silos. Big companies don’t have one data lake, they have data lakes, ponds and pools.
Recently, I had the honor of speaking with a number of the world’s most influential thought-leaders in the fields of data science, data analytics, machine learning and digital transformation. This group of prominent data technologists was more than happy to answer a wide variety of question on