Big data is an ever-evolving and dynamic term that describes large volumes of data with the potential to deliver useful insights and information. Big data can inform machine learning strategies, form the basis of artificial intelligence applications, and transform business operations.
For years, Big Data was defined by the 3 V's. Companies looked at the extreme volume of the data we collected, the variety of data available, and the velocity required for data processing. These concepts were identified in 2001 by Gartner analyst Doug Laney.
Since then, various companies have implemented their own "V's" into the big data discussion too, such as "value" and "veracity." In other words - how valuable is your data, and how much can you rely on it?
As new technologies make data more accessible, how is the big data environment changing, and what does it mean to the future of communications?
What is Big Data
Research shows that 80% of the world's data is dark. This means the information has never been used to drive business decisions. For years, the world struggled to access endless forms of information, all the way from the analytics stored in customer voice conversations, to the data in images.
Today, we're discovering new ways to collect and analyse data from almost every business touchpoint. The result is that companies can dive deeper into a range of experiences. For instance, data obtained from a workforce optimisation tool shows you where your employees are their most productive, and where they need help to boost efficiency. Data about your CCaaS strategy can show you where you have gaps in your contact centre environment, and where it may be worth building extra channels into your omnichannel environment.
Big data analytics can even help organisations to get a better sense of their customers, and the journeys they take when making a purchase. With data, you can track down all of the touchpoints where your clients interact with your business and look for ways to improve their experiences. For instance, if you find that your audience prefer SMS contact to phone conversations, you can implement an SMS strategy to update them on their order progress or shipping status.
Big data analysis can also tell you more about individual customers so that you might provide more personalised up-selling suggestions or guide them towards products that are relevant to them.
The challenge today is in accessing data, without crossing privacy and compliance boundaries. As consumers become more concerned about how their private information is used, national regulations like GDPR have come into play. These issues force companies to think more carefully about the data that they can collect, and the kind of consent they must get from clients. Businesses can't just collect data mindlessly. Information must be gathered with a specific strategy, purpose, and a high level of consent.
Big Data Trends
MarketWatch suggests that the global big data market will reach a value of $118.52 billion by 2022. Developments in the way that we can collect and store data, along with the ever-more flexible support of the cloud has helped the big data environment to evolve. All the while, we're seeing a number of impressive new trends appear in the market, such as:
1. The Rise of Open Source Processing
Open Source applications like Spark and Hadoop continue to be crucial components in the big data space. Surveys suggest that 60% of enterprises expect to have open source clusters running by the end of 2019. Many companies are looking to expand their use of such technologies for data processing purposes.