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Why Is BIG Data So Valuable?

Why is BIG Data So Valuable and are we using it the right way? Rebekah Carter of UC Today writes 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.

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.

2.      Edge computing and analytics

The demand for Edge computing is on the rise. Edge computing brings companies as close to endpoints and sensors as possible, to reduce traffic and latency in a range of networks. Gartner suggests that edge computing and cloud computing models will continue to evolve and complement each other in this year, and the years ahead. Cloud services may expand to live both in centralized servers and distributed on-premise servers and edge devices too.

Some people believe that edge computing and analytics will help to increase security and compliance in the business environment, due to their decentralised structure too.

3.      Predictive Analytics

One of the biggest benefits of big data comes from its ability to inform machine learning strategies. Predictive analytics is a solution born from machine learning. By gathering huge amounts of historical data, companies can predict everything from when a machine on an industrial floor needs replacing, to when customers may begin to churn.

Predictive analysis can offer companies of all shapes and sizes insights into what they can do to transform their business environment. Through predictive analysis, contact centres can even ensure that they’re prepared for changes in consumer trends, and influxes in calls.

4.      IoT

The rise of the Internet of Things is set to have a significant impact on the big data landscape. Gartner predicts that there will be 20.4 billion connected IoT devices by 2020. As such, the volume of data companies will be able to collect will grow dramatically. Organisations will need to implement new systems and technologies to handle the flood of information coming into their business.

Business leaders that can respond well to the IoT environment could discover incredible insights about how their products and services are used, or even how the industry overall is evolving.

Big Data Statistics

The market for big data is growing every second. We’re continually creating new information. For instance, the volume of data produced by companies in the US alone is enough to fill more than 10,000 libraries. Here are some of the facts you need to know about big data:

Big Data Hashtags Used on Social Media

  • #BigData
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  • #SmartCities
  • #OpenData
  • #MachineLearning
  • #IoT
  • #DataScience
  • #BusinessIntelligence