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
Businesses have come to expect that smart rivals wielding digital technologies will disrupt their competitive landscapes. How ready is your organization to be a digital disruptor? Take a look at detailed criteria for assessing your organization’s readiness and the strategic steps you can take to
If simplicity can fundamentally accelerate focused action, then you can significantly boost speed, productivity and effectiveness in your enterprise. Take a look at this overview of key announcements unveiled on the first day of IBM Insight at World of Watson 2016.
A recent CrowdChat covered team data science as the core competency for digital disruption in today’s business environments. Consider these highlights from that discussion as you prepare for your trip to Las Vegas.
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
Many organizations can capitalize on big data solutions and technologies to make use of expanded volumes of data for enhancing the critical decisions that drive successful business outcomes. And yet, a number of these enterprises can be inhibited from moving big data initiatives forward for a
A day in the life of data science professionals likely involves navigating the challenges and complexities of sourcing, preparing, modeling, developing and governing data, analytics tools and other assets in collaborative environments. Get a glimpse of the roles that compose data science teams and
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.
What is the key to staying ahead of the competition? Quite simply, data science. See why innovative companies have embraced the power behind data and analytics to move themselves way out in front of competitors.
Spark’s built-in machine-learning library (MLlib) provides a key differentiator from predecessor open source technologies and leverages Spark’s distributed, in-memory execution model. Take a look at some practical applications for specific Spark machine-learning algorithms in three advanced