Quite often, we see that the need for data security and governance makes some organizations hesitant about migrating to the cloud. This is perfectly understandable given the types of data gathered and used by businesses today, the regulations they must adhere to on both a local and global level,
Today’s businesses need a culture of collaboration that empowers knowledge workers to glean cognitive insights from data that help transform and modernize operations. See how cloud-based platforms and solutions enable data scientists and other experts to exploit artificial intelligence, machine
The concluding week of September 2016 offered much excitement in New York City, the backdrop for Strata + Hadoop World 2016 and several key IBM announcements, including the launch of a cloud-based, self-service environment for data science teams. Enjoy some key highlights captured from this
IBM Insight at World of Watson 2016 has oodles of opportunities for data engineers to enrich their skill sets with a bevy of best practices, peers to network with, pointers and tips to discover, sessions to attend and more. Consider five key reasons to get the green light from your organization to
The importance of data science expertise, techniques and tools in a world rapidly employing advanced cognitive systems cannot be understated. Learn more about how business analysts, data scientists, data engineers, application developers and other professionals with analytical skills sets are using
Now introducing the “Insight Ops” model. This new model will embrace and enable an agile environment for discovery and exploration and manage the transition necessary to deploy the insight to make it actionable.
As the data used by an enterprise grows in size, variety and importance, it is no longer acceptable that the gathering and maintenance of metadata remains an under-funded and neglected afterthought for data-driven organizations. Metadata management needs to become a key focus of an organization's
A variety of organizational roles interact with business data, and each role faces its own particular challenges in collaborating with its IT counterparts. In this installment of the InsightOut series, learn more about the responsibilities of these personas, exploring the considerations that govern
Organizations looking to be more data-driven than ever before not only want to pervasively enable analytics across their enterprises, but they also aim to allow for enhanced collaboration and interaction. In this second InsightOut series installment, see how they can face the challenges to
Organizations have a tool to address the multiple challenges faced by their knowledge workers: multispeed information technology. In this podcast, get an overview of multispeed IT and details on how businesses can implement it rapidly and cost-effectively.
Disruptive innovations such as big data, machine learning, cognitive computing and cloud-based services are presenting analytics professionals with rapid transformation that impacts business. As a result, organizations are adopting new best practices for data analysis processes. Dig into this first
Why is Spark so badly needed by the data science community? Primarily, it offers an open platform for fast, powerful data access that is vital for organizations because they are increasingly using a wide variety of technologies to deliver analytics, and they are tied to a variety of workloads.