Historically, big data and analytics has been a field reserved for specialists—data scientists, database managers, and the like—who focus on extracting value from data. Those days are now, well, history.
Proprietary analytics environments are giving way to open source tools, open source data sets, and free online training. We are coming to a time in which big data and analytics tools are available to anyone or any business, and are easier to use than ever before.
Today, a person with a laptop can do data analytics and visualization from the family room couch or the office cubicle. Anyone can now take an off-the-shelf computer, install dozens of free tools and datasets, and go for it. Want to compare the data from your Fitbit with the entire Fitbit database to see how you’re doing in relation to other Fitbit users? Your answers are just a few clicks away.
The mass appeal of data analytics and visualization is evident in sites like the Data Is Beautiful subreddit, which in a recent tabulation had more than 3.7 million users. The online training site Coursera, meanwhile, has more than 14 million students, including many users who are consuming the site’s free courses on data analytics from top universities. The site’s most popular courses include “The Data Scientist’s Toolbox” and “R Programming”—a popular language for data analysis.
At Intel, we love this trend. We’ve been heavily involved with big data, data analytics, and data visualization for about as long as we’ve been in business. Today, we are furthering the cause of big data and analytics by making many tools available, some of which are free for downloading.
We couple capabilities of tools like the Intel® Data Analytics Acceleration Library, the Intel® Math Kernel Library, and the Intel® Analytics Toolkit with the power and performance of Intel® Architecture. Add in a host of open source tools for the management and analysis of big data and you have what you need to bring data science and advanced analytics to life.
A discussion of the capabilities of these Intel tools is beyond the scope of this blog post. For now, the key takeaway is that countless resources are available to the masses for data analytics and data visualization.
Ready to get started? Download a tool. Take a free online course. Join a community. Start sharing your data online. You no longer have to be a pro to jump into this business. You just need a connected computer and the desire to go for it.