Remember when data was measured in gigabytes? Those days are gone. Now, we’re wanting to wrap our brains around terms like zettabyte, yottabyte, and brontobyte.
In 2015 alone, businesses generated around 7.9 zettabytes of data globally. That number is likely to significantly more than quadruple by 2020. Within most organizations, all that data is stored across multiple systems which can be overly complex and time-consuming. Just 12 percent of it ever gets used.
Employees reach their breaking point. A lot more than 90 percent admit to discarding data without fully reading it, and over fifty percent say an excessive amount of information causes their quality of work to suffer. When you mount up constantly they waste wading through data, it amounts to a complete workday each week xbox live code generator no survey.
Why? Because data without context is meaningless — and it’s bogging down employees, that are under increasing pressure to make sense of it all.
Related: Big Data Combined With Machine Learning Helps Businesses Make Much Smarter Decisions
Instead of driving business value, data is leaching productivity from many organizations. Nearly 60 percent of business leaders struggle to convert data into actionable insights, and 91 percent of companies are not capable of doing it quickly enough to drive decision-making. Often what they’re missing is context.
To understand the connection between data, context and insights, it can help to think about your organization data as a pyramid: raw data forms the beds base, formatted information provides more context, and at the top, sits the insights that will help influence business decisions.
Data alone is simply noise.
At the end of the pyramid you have all your raw data — reams and reams of unprocessed, computer-friendly facts residing in databases and spreadsheets. It’s a potential goldmine, sure, but every mine contains a lot more dross than ore.
In a period when it requires just two days to generate as much data as humankind amassed from the dawn of civilization to 2003, many enterprises are at risk of suffocating underneath the weight of their very own data and lack the employees with the advanced data analysis skills to mine it.
“Data is now ever more central to business decision making, and is extending to people who have little or no training in data use and interpretation,” says business consultant Barry Devlin.
Data today arrives in several formats that’s then stored across multiple complex systems or spread out across different departments. This is exactly why three-in-four firms say they wish to be data-driven, but fewer than 30 percent are in reality successful at it.
Raw data has limited business value without context since it fails to give employees the backdrop they have to know what it is, when it happened, where it happened, what else was going on, and so on. Throwing raw data at your employees doesn’t allow them to leverage it to its full potential — data must certanly be processed for analysis or it’ll remain largely useless.
Related: 5 Lucrative Careers That Require Data Analysis Skills
Information puts data in context.
At the middle of the pyramid lies information, or data with context. Information is an accumulation data points that help employees understand something about what’s being measured — quite simply, it answers “who, what, where, when” questions. Businesses get information by processing, aggregating and organizing their data into more human-friendly formats such as data visualizations, dashboards or reports.
“Contextualization is crucial in transforming senseless data into real information — information that can be used as actionable insights that enable intelligent corporate decision-making,” says Wired contributor Alissa Lorentz
Arming decision makers with information for analysis rather than raw data requires much less effort on their part to make sense of what’s going on. Nonetheless it still must be analyzed to determine how to proceed with the information.Read More