By Mark Melillo & Thomas Palmieri
The Internet of Things is changing how we collect, analyze and, ultimately, use data. Gartner estimates that by 2020, 25 billion smart devices will be on the planet. (Keep in mind that the current world population is only 7.6 billion.) Those machines -- embedded with sensors that gather, store and analyze information -- transmit data to us, as well as to the cloud and to one another. The sheer amount of data at our disposal could easily become overwhelming. And early indicators show companies struggling with the implementation of the necessary systems to make that data useful.
Historically, all of that information, or “Big Data,” was structured data: It was analyzed and a conclusion was drawn. But today, there are different types of data being captured: video, unstructured communications, Internet of Things sensors, etc. And it all has to be analyzed using today’s technological infrastructure. For example, flash technology has been around for a long time, but a new interface storage standard, Non-Volatile Memory Host Controller Interface Specification (NVMe), is designed to conduct memory transfers at sub-millisecond latencies. Therefore, huge amounts of data sitting in memory are now available in real time. Using the appropriate technology will keep us from drowning in data.
Thousands of products and solutions are on the market measuring, monitoring and collecting information from all sorts of devices and gadgets and applications and we can now bring all that data together into one cohesive, complete picture. We can look at that data from various angles at any time, and we can act upon what it is telling us. Big Data’s reached a point where the sky is the limit. We can bring the data coming from anywhere at any time, we can store it, we can prepare it for quick searches and access and we can get immediate value from it.
Yet despite all the evidence that big data has the power to beneficially transform the enterprise for the better, organizations continue to struggle with implementation. Focus areas for Big Data initiatives, such as efforts to decrease expenses through operational cost efficiencies, have proven to be successful 49.2 percent of the time – which means that roughly the other half of the time the implementation fails, according to a New Vantage Partners survey.
Meanwhile, we are seeing more new applications for analytics: For example, consider the importance of video today. It used to be that people only wanted to know when someone came in and out of a building from a security standpoint, and video was used to capture that information. Years ago, such analog recordings were meant to be reviewed only if a problem arose, and generally recorded in a loop, creating new content and replacing the old recording every 12 hours or so. Now, everybody wants to see every piece of video. Generally speaking, there’s video of everything that happens in this country or around the world -- and there’s somebody who wants to analyze it. But businesses need the right tools to succeed in accomplishing their goals of cutting costs and performing accurate and timely video data analysis.
The tools are available, but adoption is lagging, which may be at least partly responsible for the mediocre success rate of implementations. The New Vantage Partners survey found that only 27.9 percent of respondents reported success establishing a data-driven culture. More work is clearly needed to promote the IT solutions that will let businesses drill down into the mountains of their data and quickly and efficiently.
In the future, the focus will be on adopting infrastructure that will raise the success rates of analyzing and using data. Those tools are designed to help businesses mine structured as well as unstructured big data that is stored on multiple sources, including APIs, relational DBMS and similar platforms. With search and knowledge discovery tools, such as cognitive search, businesses can isolate and use this enormous amount of information to their benefit. Big Data is changing the world.
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