When we talk about Big Data, we’re talking about a huge volume of structured and unstructured data. This data has the potential to help companies improve operations, as well as make smarter and faster business decisions.
Big Data is the large volume of data that organisations use every day. However, the sheer amount of data is often so huge that it becomes difficult for companies to process all the information, especially when using outdated techniques and traditional software or platforms.
When data is collected, formatted, stored and analysed, the company has in its hands very interesting information that can help them increase revenue, prospect for new clients, and build loyalty among existing customers.
What is Big Data analytics ?
Data analytics is used in many industries to help organisations or companies make better business decisions.
Big Data analytics can lead to more effective marketing strategies, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organisations, and many other business benefits.
Companies from all types of industries use Big Data Analytics (including in sectors like insurance, banking, automobile, healthcare, etc.), and adapt this data to their businesses and departments, such as marketing, operations, finances, IT, etc.
Thanks to the development of Big Data, companies and businesses have become more effective and better performing. Why? Because they can analyse all the information and data they may need about their customers and leads in advance, while simultaneously optimising and improving their relationships within their organisation.
Why is Big Data Analytics useful?
It allows organizations to find answers related to many issues: reducing cost and time, developing new products, making smart decisions, and optimizing processes. The combination of big data and powerful analysis is an opportunity for companies to create value.
By using Big Data Analytics, companies have more data control, which results in more precise analysis. Making decisions using these analyses can simplify operational performance, minimize risk, and ensure cost reduction.
Big Data Analytics is a new competitive advantage. The use of big data analytics is becoming an essential way for companies to perform to the best of their ability.
Companies also use Big Data Analytics to respond quickly to their customers’ needs, as well as give their potential future customers personal attention and make them happy, thus building long-term relationships to increase customer loyalty.
What are the advantages of Big Data Analytics?
- Faster and better decision-making
Big Data Analytics has always involved attempts to improve decision making. Large organizations are seeking faster and better decision-making processes with big data analytics, and they are achieving them.
- Cost reduction
Using data on results, profits, and the company’s ROI, the use of Big Data Analytics allows for better performance and lower costs.
- New products and services
The most interesting use of big data analytics is creating new products and services for customers. Online businesses have done this for many years. Now, with big data analytics, even large offline businesses can also create an ever more complete set of products and services aimed at satisfying their customers.
To analyze large quantities of data, Microsoft recommends using Power BI for Office 365, a program that offers a suite of business analytics tools that allow you to analyze data and share information. These tools can also monitor the company’s activity and provide quick responses with comprehensive dashboards available on any device.
Overall, this is an analytic solution that can help any business or organization interested in getting a complete picture of their activity through interactive reports. If you want to know more about Power BI, get in touch now!
The challenge when it comes to Big Data Analysis is ensuring that the data is used to help achieving new business goals that used to be impossible. Thanks to technological advances over the last few years, this quantitative change has also led to a qualitative change.