The increasing deluge of data, whether it is structured, unstructured, or raw data with huge volume or velocity, is leading enterprises to digitize their business-critical processes. CIOs need to focus on the concept of harnessing organizational data to add business value. They can achieve it with the help of the implementation of Big Data Analytics for faster intelligent decision-making. Having the right data at the right time will enable the right business insights, which will facilitate smart planning & thereby boosts the business performance largely.
However, the process of effective data utilization is a decisive task and still trending. Businesses need critical insights for faster intelligent decision-making and real-time execution. Analytic models can be built on the available data to unleash business insights and achieve strategic business goals. Integrating Big Data Analytics implementation in the existing business models can create the potential to produce tangible results, which can truly empower the organization for enterprise-wide business transformation.
Gartner’s report indicates that 25% of large organizations will be a buyer or seller of data by 2020. This confirms that CIOs are gearing towards employing big data analytics implementation as part of their strategic planning to achieve digital transformation. Let’s take a walk through few use cases where Big Data Analytics implementation has bought an unprecedented transformation.
1. Prediction Analysis and Business Optimization
Big data enables the business to collect the raw data, structured or unstructured data, from different sources. With the implementation of big data predictive models and machine learning technologies, the prediction of customers’ behavior and machine failures are possible. As a result, the businesses can optimize their strategy by offering a discount, other promotional offers, or even suggest other products for purchase. Also, they can carry out predictive maintenance of equipment before they fail.
2. Understanding your customers further
Big data analysis enables businesses to recognize their customers by realizing their thought processes and feedback beforehand. The companies can align their strategy accordingly. Furthermore, businesses can minimize complaints and address the dispute before it makes customers unhappy. Several big data analysis tools are available in the market that forecasts depressing emotions; thereby helping businesses to act immediately on them to diminish.
3. Better insight means better strategy
Nowadays, all types of data are pouring everywhere. Whether it’s social media, smartphones, sensors, websites, search engines, gadgets, messages, videos, and much more. Analysis of these data can give insights into individual habits and activities. Furthermore, multiple departments store such kind of data but individual departments do not know the facts of others. Big data analysis can provide deeper insight from different data sources in a unique way that is more helpful in defining the strategy overall.
4. Enhancing the customer experience
The emotion of customers is significantly important for the success of any brand. Through big data analysis, businesses can know how customers feel and connect with them emotionally gaining their trust. Furthermore, businesses can improve the services and save the customers’ time by optimizing the processes. For example, Businesses can choose the closest warehouse to the vendor/customer to fulfill the order. It saves around 10% to 40% shipping cost and fulfills the order faster.