Analysing big data is the buzz word for the couple of years in the IT world. This analysis has been assumed to become the trend of the enterprises looking to gain insights into business operations and find patterns between sales and marketing activity against revenue.
The volume, variety and velocity of data coming into your organization continue to reach every single level. This phenomenal growth means that not only must you understand big data in order to figure out the information that truly counts, but you also must understand the possibilities of big data analytics.
Many organizations are using it to get benefited by big data. Many big enterprises are using analytics to create a database that consolidates residents’ data to reduce fraud and costs, while some are using it to better understand what its customers are buying.
Open source frameworks like Hadoop is making the storage of data more cost effective and, with various analytics tools on offer, which is the indication of the golden time of big data is now.
But this scenario is going to change. Because many organizations are using analytics of large data set only to take a look at what is happening or has happened across an organization. This data is being analyzed into insightful information that highlights sales opportunities or problems in a supply or manufacturing chain.
This analytics is helping organizations to be more successful. But the future of big data is getting founded by cloud computing, machine learning and in-memory technologies, giving us insightful in the future.
Future trend – Crystal ball analytics
The next big trend in the big data will be predictive analytics. The use of analytics does not confine only to have a look at the insight, but they can also use it in a combination of real-time, historical and third-party data to build forecasts of what will happen in their business months, weeks or even just hours in advance.
This use of analytics will be beneficial to avoid predicted problems, such as equipment failure or depleted stock, or to capitalize on opportunities to market products to customers, like targeting people in happy or dejecting moods after a sporting event.
The way predictive analysis have become so easy today, like never before. It has become so relevant and easier to use, and offers ways for forward-thinking enterprises to succeed in the competitive world.
Customer relationship management (CRM) software
Predictive analytics can be very effective in the area of customer relationship management (CRM) software. People working in sales and marketing can use analytics to forecast the impact of their activity and provide more personalized pitches or content to individual customers. It will be more convenient to them as they don’t want to depend on historical data on previous interactions, like customer data and customer interaction, access business information and automate sales.
Option of the Predictions-as-a-service
Some machine-learning and analytics technology specialists are using data not just analysis but also for making predictions, with a cloud-based predictive analytics service operating at a ‘hyper scale’.
This system takes CRM data from various platforms and analyses it against over 100 billion anonymised sales interactions taken from across its global customer base. This enables greatly expanded and enhanced predictive analytics, as a company’s internal data is compared against an aggregated mass of data.
This also enables an organization to see how it is performing against larger regional and global sales trends in its sector and understand how influences such as current events, economic factors and even the weather have affected its sales pipeline. This kind of analytics is the next big evolution in big data and cloud computing.
This only clears the myth that all this is not about big data, but how you use big data. It’s very clear that a crystal ball rather than reflective approach to big data is the future of technology-savvy enterprises not content to keep looking behind them.