Big data is defined by large quantities of data. There isn’t an exact unit of measurement to classify what is or isn’t big data, but this is somewhat intentional. The “quantity” of data, as it relates to big data, isn’t solely dependent on the shear volume or size of the data – big data also depends on the quality and propensity it has for analytics.
Business decision-making is heavily reliant on information such as: numerical databases, text documents, videos, audios, transactions, and everything in between. Regardless of the format, big data serves its job as the foundation for information to be aggregated and analyzed, providing meaningful insights.
With so many use cases and possibilities for big data in our current and future society, it’ll be better understood from this list of the top 10 most informative facts about big data.
Successful businesses have always been data-dependent. Data, however, is best analyzed in digestible amounts. Most companies base their business model on a few or singular offering(s) and this serves to narrow down what type of data that analysts need to go after.
However, traditional data analytics would have a hard time handling the massive amount of data that is being generated through today’s proliferation of connected devices and sensors. It is much harder to look at the metadata, or the information about data, when there is so much to process that you lose sight of your goal.
As previously suggested before, there are many types of data. Aside from the various forms of data that you may have learned in grade school, such as binomial data, nominal data, continuous data, qualitative data, etc. – there is also different types of data for the enterprise that defines prescriptive analytics, diagnostic analytics, predictive analytics, and so on.
The role of the chief data officer is being defined by the exponential progress of big data analytics. Businesses are keen to acquire a CDO whose job is to dominate data ingestion by bringing clarity to key objectives and improving upon business strategies – all while staying mindful to the growing toolkit of the CDO.
Organizations with foundations built on data should be wary of digital attacks that could otherwise topple them. One example of a costly cyber attack took place in 2017 to Equifax, where almost 150 million personal accounts were compromised and sensitive financial information were leaked.
Machine learning is a big topic to cover on its own. If you’re interested in learning more about machine learning (pun intended), check out our other article here.
In short, machine learning is a system that uses data as a sort of “fuel” to solve complex problems. The more quality data that is fed to the machine learning algorithm, the better the solution it provides.
The daily production of data is pushing limits that challenges conventional measurement efforts. Google logs about 3.5 billion searches per day – resulting in 1.2 trillion searches per year.
No one could’ve predicted the level of elite digital marketing efforts by Google or Facebook. This level of marketing and other uses is made possible by great analytical leaps in how we interpret big data.
Monetization strategies with data analytics can be tricky but if done right, companies could turn actionable insights into real profits. In fact, just a 10% increase in data accessibility converts to an estimated $65.7 million for the average Fortune 1000 company.
An efficient cloud infrastructure allows businesses to adopt big data analytics. With huge influxes of data, it’d be a necessity for organizations to organize and safely store all this potential value. For businesses with a growing appetite for bandwidth efficiency, cloud computing offers flexibility, control, security, and other attributes that ultimately improves both workflow and cashflow.
Big data will soon become ubiquitous in the backyards of many industries. A recent report indicates that the big data market will see a 10% CAGR, or compound annual growth rate, from 2017 to 2020. This amounts to a growth difference of 20 billion dollars between these years.
Big data isn’t going away any time soon. In fact, it will soon be commonplace in business of all sizes. The capabilities of big data analytics are too powerful to be overlooked. That being said, only approximately 73% of organizations have invested in big data – and undoubtedly, a fraction as much have only begun to fully utilize its capabilities.