It should come as no surprise to say that today, the world is drowning in data.
By some estimates, each day, 7.5 septillion (that’s right, “7.5” followed by 24 zeros!) gigabytes of data are created. To get a tangible sense of how much data is generated, consider this; according to the World Economic Forum, each day, “500 million tweets are sent, 294 billion emails are sent, 4 petabytes of data are created on Facebook, 4 terabytes of data are created from each connected car, 65 billion messages are sent on WhatsApp, 5 billion searches are made.”
It’s hard to grasp these massive volumes, but what’s important to recognize is the potential value they hold. For example, when it comes to criminal and terror investigations, the data can potentially contain clues and insights that may help government and enterprise security teams resolve investigations faster, and with more accurate results.
The challenge is that the vast majority of the data is “dark data”, or data that is never properly analyzed.
To combat the issue of dark data analysis, businesses and governments have attempted to use analytical tools to explore data and draw out key insights. But despite their best efforts, they still fall short. To quote McKinsey & Company, “Few dispute that organizations have more data than ever at their disposal. But actually deriving meaningful insights from that data – and converting knowledge into action – is easier said than done.”
What is the real challenge of data analysis?
At Cognyte, we recently conducted in-depth research on the challenges preventing security organizations from fully leveraging the data they have access to in order to generate actionable insights.
So why are organizations unable to tap into the deep insights that their data could, in theory, provide?
Is it the volume? Digital transformation has transformed every aspect of our lives, generating a flood of data. While the huge volumes of data certainly play a part in the challenge, there are other factors which are more complex to deal with.
The Variety of Data
First there is the fact that the data comes in numerous types and formats from a dizzying array of sources. The data comes from social media platforms, financial transactions, government databases, cyber and forensics sources, Internet of Things (IoT) sensors, devices and countless other sources, and can consist of text, audio, images, videos, logs, and geospatial data, to name just a few. Even if we focus exclusively on social media platforms, as an example, consider that the average Internet user has 8 different social media accounts, with users aged 16-24 having 9 accounts! This data diversity makes it difficult to fuse the data into a unified layer that can be analyzed to extract insights.
Adding to the challenge posed by the immense variety of data, is the fact that the data is typically stored across siloed databases, both inside the organization and in external sources. The data must be fused together before it can be processed and analyzed to generate insights.
The Value of Your Data
And finally, what is the value of all this data? In other words, now that you’ve got all this data, can it be translated into insights that make a real impact? Can your analytics solution help your team stop the next malicious attack or prevent insiders from compromising your organization’s business continuity?
Analytics that Works
Government and enterprise security teams have long tried to “connect the dots” using analytics tools, but they typically relied on home-grown, proprietary solutions. But these tools are no longer sufficient to overcome the data challenges outlined above.
As a result, security organizations are increasingly adopting open security analytics platforms that can overcome these challenges to generate actionable, timely insights needed to reach resolutions faster and with greater accuracy.
To learn more about unlocking the potential of your organization’s data and generating high quality dark data analytics, download our new report today.