What is Big Data?
Big Data describes a large volume of rapidly expanding data which comes in structured, unstructured and semi-structured forms. This data is generated from devices connected to the internet and is being gathered consistently from new data sources.
As the volume and extensiveness of the data are vast, traditional data processing software and software management tools are not adequate on managing it.
What can Big Data offer?
All organizations who have the task of handling large amounts of data will need to manage their data effectively to maximize its benefits.
Big Data can provide insight into many industries attempting to understand target markets and solve current problems. I.e. Companies trying to boost sales or introduce new products/services can use big data to seek and understand consumer purchasing wants and needs.
Big Data can also conduct predictive analysis and help frame business strategies by seeing and extracting relevant information in data sets.
By combining AI’s self-learning capability with advanced algorithms, companies can predict possible future scenarios which may have been unforeseen otherwise.
Predictive analysis allows businesses to make smarter, more informed business decisions based on what most likely will happen next. This information is critical for predicting trends and undiscovered patterns in their market.
Furthermore, Big data is not only limited to marketers and businesses selling products but can also provide insight to healthcare professionals, environmentalists, cybersecurity professionals and robotic engineers.
For example, healthcare professionals can gather data which build comprehensive patient profiles, improving personalization and efficiency.
It can also prove cost-effective for businesses when it comes to storing large amounts of data. Big Data technologies such as Hadoop and cloud-based analytics offer this service.
The Three V’s of Big Data
Dough Laney introduced the concept of the Three V’s in the early 2000’s. Big Data with the volume and variety of data it possesses can be challenging to understand; the three V’s simplifies this into three segments, which are:
Volume
The first V describes the copious amounts of data currently available, as the name ‘Big Data’ implies.
Ninety percent of all data has been generated only in the past two years, and the creation of around 2.5 quintillion bytes of data occurs daily, resulting in a greater need for hard drive and cloud solutions. When companies fail to properly destroy their discarded hard drives, they’re putting their security at risk. This is why you need to protect your business by ensuring that the sensitive data stored on your discarded hard drives can never be accessed. Reformatting or electronically erasing a hard drive is not sufficient since important financial records, confidential employee information, and internal documents can still be retrieved. Physical hard drive and media destruction is the only way to completely remove all traces of data from a hard drive and any type of media.
Businesses globally collect enormous amounts of data which will influence business strategies and deals, investments and their social media. The more data you have at your disposal, the more potential value it can have for the organization using it.
Social media has significantly impacted big data as currently there are 2.41 billion monthly active users worldwide with 1.59 billion users logging in daily.
As the number of Facebook users continues to grow, so does the amount of personal data the platform collects, with trillions of posts already made and photos uploaded everyday.
Facebook is not the only social media platform to provide data. Other platforms such as Twitter data feed and website or mobile app clickstreams also have data which may be useful.
Plenty of other companies outside the social media sphere can make use of Big Data as well. For instance those offering student loans can make use of this as well.
Velocity
The second V is Velocity, and this refers to the speed of data being generated. Once the data is generated the rate of it being received and processed determines the potential value of that data.
As the volume of streamed data is massive while coming from various sources, the velocity of which Big data processes this information is significant. Some of these sources include social media sites, online purchases or products or services, applications where users input their details and many more.
Harnessing the processed data, however, can prove very challenging, as the data continuously coming in is so large it can quickly outpace the ability to understand it.
Every two years, the volume of data doubles, meaning that growth is exponentially fast.
Another factor is that not all of this data is allowed to be analyzed. Certain information is tagged and classified as it is deemed to be too sensitive or unsafe, data teams handling this try to identify the potential risks.
The receiving and processing of unprecedented data should be as efficient as possible, realizing its exact value; this is why the velocity of Big Data is vital. With this you can tie together data about someone sending money abroad, someone taking a job on the other side of the world, and the weather.
Variety
The final V of big data is Variety; this refers to the many types of different data available.
This type of data is diverse and isn’t limited to structured data which can be stored, processed and accessed in a fixed format. Structure data generally comes in the form of a database containing information already organized.
Unstructured and semi-structured data, on the other hand, include additional data forms such as images, videos and text files. These require preprocessing to understand its meaning to support metadata.
Conclusion
A business analyzing Big Data has the potential to gain invaluable insight, which will help them achieve their strategic short term and long term goals.
By analyzing large amounts of data from various sources, businesses will have the benefits of:
- Learning consumer preferences by understanding buyer habits. Understanding this can help market trends to be spotted and enables for better customer interaction and engagement.
- Predict future outcomes using predictive analysis; businesses can make more educated decisions and change their strategies if necessary.
- Cost-effective as Big Data management tools such as Hadoop and Cloud-Based Analytics can store large amounts of data.
- Allowing businesses to monitor customer feedback. Understanding consumer concerns and needs businesses can make adjustments regularly, improving online presence and overall reputation.
