r-big-data

  • Why Do We Use GPUs for Machine Learning

    Why Do You Use GPUs Instead of CPUs for Machine Learning?

    GPU vs CPU Admittedly, discussing the differences between CPUs and GPUs is a rather elementary concept for technologists, but it’s an important exercise that helps us better understand what drives modern Artificial Intelligence. Although GPUs are traditionally used to compliment the tasks that CPUs execute, they are, in fact, the driving force behind your AI […]

  • Analytics Maturity Assessment

    Using Analytics for Annual Planning

    When people hear the word “analytics,” they tend to get nervous—especially when it’s coupled with other words like “algorithm,” “GPU,” and “deep learning.” And they automatically think that the subject matter is beyond their understanding (or even their IT team’s abilities). However, analytics doesn’t have to be impossible or “beyond your current capabilities.” Your company […]

  • Data Ingestion and the Data Value Chain

    Purposeful Data Ingestion: What You Need to Know About the Data Value Chain

    Previously, we discussed the three fundamental branches of analytics as well as how each one successively breaks data down into more manageable pieces. In today’s installment, let’s continue the data ingestion conversation by discussing the different components of the Data Value Chain. Let’s Get Back to Basics The Business Dictionary Online defines a value chain […]

  • Democratize Your Data

    Enabling Decision-Making at the BU Level with Analytics

    Housing untapped, raw data does little but expend additional storage and security resources. But, at the same time, accessing that data for active use is hard. Because of this, many companies have started working through their database administrators (DBAs) to try to get more from their data. However, as is the current trend, organizations are […]

  • 5 More Unexpected Ways that Big Data Augments our Reality

    5 More Unexpected Ways that Big Data Augments our Reality

    As we mentioned before, there are seemingly limitless ways that Big Data can augment our realities, and we believe that it is important for you to understand how these analytics work behind the scenes in our everyday lives. If you have read the previous post, then you hopefully noticed the undeniable trend that runs throughout […]

  • Machine Learning Applications

    Machine Learning Applications: The Good, The Bad, and The Unrealistic

    The Latest Innovations and Controversies of Machine Learning Up until the 1950’s, computers needed incredibly detailed commands, in highly-specific languages, to accomplish even the simplest of tasks. By 1959, Arthur Samuel had developed the Samuel-Checkers-playing Program—a computer game that became the world’s first ever self-“learning” machine. Rather than pre-program his computer to tell it what […]

  • Enterprise IoT Solutions

    Not Just a Buzzword: Enterprise IoT Solutions

    Today, we return to our ongoing analytics conversation. If you are new to the discussion and want to get caught up, consider revisiting our posts on the three fundamental levels of analytics as well as the analytics implementation learning curve that the tech industry is currently experiencing. For those who are caught up, however, we […]

  • Business Data Analytics

    Real Talk About Business Data Analytics

     

    The majority of companies don’t realize that they can answer many of their business questions with the data that they already have. It’s just a question of being able to access it.” — TSA Enterprise Solutions Architect, Corey Gary

    In a previous blog post, we discussed the three basic levels of analytics—descriptive, predictive, and prescriptive—and explained how this technology is architected to break down massive amounts of raw data into more manageable, actionable chunks. With modern business data analytics, researchers and technologists no longer have to “drink from the fire hose” of raw data.

    However, it is important to establish that analytics is not simply a “wind-up-and-let-it-go” apparatus; it requires more resources than its current IT buzzword-status may have you believe. As a result, many companies are underutilizing the data at their disposal.

  • 5 Ways That Big Data Augments Our Reality

    5 Ways That Big Data Augments Our Reality

    We live in the Digital Age. An age where you can’t do a quick Google search for “cheap flights to Utah” without ads for Kayak.com or Zion National Park popping up in the margins of your web browser for the next two months. And while retargeted ad campaigns can pose as mild annoyances, the insights […]

  • 3 Levels of Analytics: Making Big Data Bite-Sized Again

    The birthplace of analytics was not, in fact, in a techie’s basement in Silicon Valley or in some state of the art computer lab; rather, analytics first made its debut in Athens, Greece in 335 BC, thanks to the teachings of Aristotle himself. As such, reason was officially introduced to an awakening intellectual world. Scholars […]