Big Data Analytics is a hot topic. Since 2011, the interest in Big Data Analytics has grown significantly and it’s set to get even bigger in the next 5 years. According to the IDC “Over the next five years spending on cloud-based Big Data and analytics (BDA) solutions will grow three times faster than spending for on-premise solutions.”
Examining data is not a new concept – businesses have been doing it for years to try and gain a better understanding of how to better sell to their customers. What is new, however, is the number of data streams and the speed in which it is produced. IBM describes Big Data as data sets whose size or type is not compatible with traditional relational databases. Big Data Analytics is essentially the analysis of these very large and diverse data sets that include structured and unstructured data.
Now that we’ve firmly entered the digital age, businesses are reinventing themselves and migrating over to a virtual online world. The way we do business has changed, now we have multiple streams of information that are constantly producing data for us to analyse. Peter Sondergaard, senior vice president at Gartner, recently said “interconnections, relationships, and algorithms are defining the future of business.”
The biggest factor in the growth of Big Data Analytics is the rise of the Internet of Things (IOT). The UK’s Government Office for Science predicts that by 2020, the number of connected devices could be anywhere from 20 billion to 100 billion. The amount of data that is being produced from structured and unstructured objects has fuelled software companies to build a platform that can quickly and efficiently analyse Big Data giving businesses useful insights and trends to help them make key decisions.
What is the future of Big Data Analytics?
There are two types of data streams: structured and unstructured. Structured data is usually in text format and is displayed in an orderly fashion. All data is labelled, easy to access and can be easily analysed.
Unstructured data is essentially the opposite of structured data. It is binary data that has no structure to it. Examples of unstructured data include photographs and video, scientific data, mobile data and data produced from social media channels.
We believe the biggest area for growth in Big Data Analytics will be the analysis of unstructured data. IBM Watson has recently made significant in-roads into the world of unstructured data and offers businesses the ability to analyse data from a variety of unstructured sources. According to Watson, 80% of all data today is unstructured.
Exciting projects like using Big Data Analytics to enhance non-player character interactions in games, or the news that IBM Watson is working with Apple to provide Apple watch users a good nights sleep, only mark the start of the innovative projects that will result in the ability to analyse unstructured data.
So where does it end?
The short answer is: it doesn’t! The Internet of Things is set to explode with Business Insider predicting that by 2019 the Internet of Things will be double the size of the smartphone, tablet, and wearable market. So the real question every business should be asking is: how can I jump on the bandwagon and make Big Data Analytics work for me?