Interested in learning what it takes to operate a start-up? On this episode of Making Data Simple, host Al Martin sits down with Simon Lightstone, IBM offering manager, to discuss what it took to get his startup off the ground. Simon offers tips to those facing a similar experience and describes
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.
Back by popular demand, Tanmay Bakshi returns to the Making Data Simple podcast to update our listeners on his groundbreaking work applying AI and machine learning to the healthcare industry. From exploring EEG patterns to enable people to communicate without speech to predicting adverse reactions
Two of the the most popular IBM podcasts collide in this special episode of Making Data Simple. Host Al Martin interviews William McKnight, president at McKnight Consulting Group and host of the Data Decoded podcast. Al and William discuss the pros and cons of big business versus consulting, trends
Oracle generated a lot of buzz prior to Oracle OpenWorld 2017 last September with their announcement of the world’s first self-driving database - Oracle Autonomous Database. However, not many details were released at announcement time. Now that the first Oracle Autonomous Database service,
IBM Hybrid Cloud Marketing VP Scott Hebner speaks with Big Data and Analytics Hub about the bets he’s placing on the offering to evolve into the company’s first AI platform and emulate WebSphere’s success.
This week on the Making Data Simple podcast, Sriram Srinivasan – architect and senior technical staff member for IBM Data Science Experience – discusses how to build and nurture trusted analytics to better your business. Sriram also shares insights on IBM Cloud Private for Data.
Data can be an organization’s most valued asset, providing insights that help strengthen business. Knowing what works and what does not can help you invest more resources in what would work in the future. Learn more about the Watson Knowledge Catalog.
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
So what happens now when we go beyond the frontiers of the data warehouse and into the world of the data lake? – the world of Hadoop, of NoSQL, the world of schema on read, of discovering the data as is? For many organizations, the holy grail is to reap the benefits of the data lake while retaining
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,