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
The media and entertainment industry faces rising challenges when it comes to the delivery of over-the-top (OTT) content—audio, video and other media streamed over the Internet. Take a look at two key issues that are at the root of these challenges despite the advanced analytics platforms that
Smart predictions can spell the difference between whether your company succeeds wildly or falls by the wayside. Get the details on four strategic pillars for smart, proactive business through predictive analytics deployment in a series of new blog perspectives.
When looking for course-changing insight, connecting the dots of information can range from meticulous exercises to bursts of inspiration. However this wow-factor insight may be derived, it can take organizations and industries on a new trajectory characterizing the dawn of an era in which
Today, more than ever, businesses need to put the ability to analyze data into the hands of business analysts, data scientists, stakeholders and decision makers. Take an evolutionary look at how Apache Spark and big data discovery are just beginning to open up a diverse and powerful set of
Creating a visualization whose design serves its intended function—rather than the other way around—can be intoxicating, but don’t get so high on data that you lose sight of your audience. Find out how including too much information can neutralize your visualization—and your message with it.
As we’ve learned, choosing an appropriate level of detail lays the foundation for an effective visualization. But if you simply take your first design idea and run with it, you might be doing your data a disservice. Find out why redundant visualizations can turn detail into too much of a good thing
Insight 2015 adds some Hollywood-style splash to its concluding general session with a big acquisition announcement that promises to take cognitive innovation to new heights. Get a glimpse of the conference’s wrap and some noteworthy highlights that punctuated this year’s event.
Apache Spark provides a processing framework that is well suited for collaboration among data scientists, developers and data engineers who create highly adaptive solutions. Attendees at Insight 2015 can learn much more about the Spark framework that is built for speed, ease of use and
So you want to enter the data science field, or maybe you are already a data scientist looking to expand your horizons. Several routes into the profession can provide the core skills, knowledge and best practices necessary to become a developer in the era of cognitive computing. And events such as
Apache Spark is exploding as a worldwide phenomenon since its origin in the Silicon Valley area of California. Find out just who widespread its adoption has grown in a survey of global examples, a wide array of community participations and upcoming event opportunities.
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.
What are your big data requirements? Determine which type of Apache Hadoop user you fit most closely. Take a short quiz to see what kind of Hadoop user you likely are and what you likely need from Hadoop to be successful.
Data scientists may be of a different breed from other analytics team members, but they are essential for bringing to the table curiosity about data and an unquenchable thirst for finding patterns and relationships in that data. Discover how combining the roles of data scientist, business analyst,