Some dispute that their organizations possess more data than they ever wished to have. And, deriving the meaningful insights from the data is not easy enough. Lots of data on board tell it’s time for Big Data services. The organization should enrich data and pay attention to the data less focused before. This article tells how different enterprises use Big Data & Analytics.
1) Create Good Customer Experiences
Customer experience is important for every industry. And, Big Data & Analytics techniques help to deliver the best experience. Even a simple product can result in a complex problem, complicating the overall customer experience. Here is where Big Data solutions simplifies the process by analyzing the different possibilities before a problem arises. These solutions take out the complexity. Also, they keep a check if the resources are efficiently used. This enables a good rapport with customers as well as efficient resource utilization.
2) Enhance Asset Performance
Big Data & Analytics enable the maximum performance of company assets. For example, a digital wind farm uses analytics to optimize the mechanical performance. And, a power generator can use the same wind that has come through, by having the turbines spin on their own. This enables the power generating company to understand how they can optimize the level of wind. Also, it would help to generate more energy with less wind.
3) Better Decision Making
Big Data tools help businesses to make smart decisions. Unfortunately, organizations are data-based and not intuition-based. Data democratization is adopted across the organization to explore data. This helps everyone in the company to answer every business question.
Walmart is one such example where the organization provides its employees access to data in a controlled way. Walmart’s Data Café is an analytics junction where heaps of internal and external data are used to get valuable insights. Teams across Walmart are invited to post their questions and problems on the Data Café for a data-based answer. So, employees can quickly drill into the data and identify the root cause of an issue. Then, they can proceed with the resolution.
4) Improve Business Operations
Big data and automation have transformed the way companies operate today. For example, chat bots use automation and big data to assist customers and answer their commonly asked questions. The chatbots can solve the issues of many customers quickly based on the evidence from the data history. Big data adds strength to automation and helps to complete time-consuming tasks. This helps skilled workers to free up. And, it results in more creative works to add greater business value.
5) Save money
Big data is not just about better business processing and decision making. Also, Big Data is used to create a channel for additional income. For example, financial service providers focus on both business and customers. They leverage the data created by financial transactions to bridge businesses and customers. Big data services for businesses include online trend analytic tools and benchmarking tools. They help the executives to know how the business is performed compared to the competitors and what are the market trends. Big data helps financial service providers to save money through data-driven fraud-detection methodologies. This helps them to identify and prevent fraudulent transactions, thereby saving billions of dollars.
6) Collect market intelligence
Data starts to accumulate once businesses start to happen across companies. The quantity and diversity of the data would keep on increasing every year. Every company will gather more insights and they will learn better on what customers expect and what customers currently have. Gathering the customer expectations and feedback can also help to mold what the enterprise has to offer and align the business approach.
7) Audit threats to safeguard data
Big Data & Analytics tools enable enterprises to map their complete data landscape. Also, this enables them to analyze all sorts of internal threats, while safeguarding sensitive data. It also helps to organize the data and keep them in compliance to different regulatory standards. Also, this feature is useful for financial organizations dealing with credit and debit card information, where data safety and protection is the top priority.