Big Data
use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data
https://en.wikipedia.org/wiki/Big_data
Big data provides insights we could not discover by analyzing data on a smaller scale.
Big data frees us from the limitations of using small samples of data to represent whole populations.
This is the inherent problem with sampling: when you begin to examine smaller and smaller subgroups of data, you will quickly find that you have insufficient observations to draw any meaningful conclusions.
Vast sets of messier data can be more useful than smaller, more accurate ones.
The size of the data-sets we can have with big data allows us to be more forgiving in terms of inaccuracies in the data; having such a large proportion of the available data minimizes the effect of any inaccuracies.Vast sets of messier data can be more useful than smaller, more accurate ones.
Big data does not tell us why two things are related, just that they are, but even this is often good enough. one of the implications of big data is that we donāt need to develop our own theories about cause and effect and then test them out. Automatic analyses of all the data can deliver correlations we never even thought of looking for.
Although data is generally collected for a specific purpose, there are often secondary applications that hold even greater value.mobile phone companies amass real-time location data from their users as part of routing calls. This data has numerous potential uses, from monitoring traffic-flows to delivering personal location-based advertising.
Anyone can spot new opportunities to create value from the data around them — you just need the right mindset. Owning vast amounts of data is not much use if you donāt know what to do with it. Equally, having the skills and tools to analyze data is of little use if you donāt own any data or donāt know where to get it.
Combining sets of data can create greater value than the individual parts.
This is also true for data-sets: sometimes their value becomes apparent only when combined with other data-sets. Trends can then be found in the newly combined data that were not discoverable from the individual data-sets alone.
Combining sets of data can create greater value than the individual parts.
Online services such as Facebook record everything we do on their sites and use this data to enhance the service they offer.
Smart companies are already tracking everything we do online, including where we move the mouse and how long we hover over items. This information is referred to as data exhaust and is used to optimize the fine details of products, such as the size and placement of buttons.
The examples show that companies who have both grasped the art of recycling user data and implemented it into their systems can enhance the service they deliver.Online services such as Facebook record everything we do on their sites and use this data to enhance the service they offer.
Think creatively to extract the hidden value from the data around you