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of data is often so huge that it becomes difficult for companies to process all the information, especially when using outdated techniques and traditional software or platforms.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 increasing revenue, prospect for new clients, and build loyalty among existing customers.

What is Big Data analytics ?

Big Data Analytics, a Business Intelligence service

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 organisations to find answers related to many issues: cost reductions, time reductions, new products development, smart decisions and processing optimization. The combination of big data and powerful analysis is an opportunity and a possibility for companies to create value.

By using Big Data Analytics, you will have more data control that surely will result in more precise analysis. The decision making could simplify the operational performance, minimising risk as well as assuring cost reduction.

We can define Big Data Analytics as a new competitive advantage. The use of big data analytics is becoming an essential way for companies to outperform their activity.

Companies also use Big Data Analytics to respond quickly to their customer needs, treating their leads individually and making them happy, building long-term relationships, so that costumers become loyal towards the company.

What are the advantages of Big Data Analytics?

  1. Faster and better decisions

Big Data Analytics has always involved attempts to improve decision making. Large organisations are seeking for faster and better decisions with big data analytics, and they are finding them.

  1. Cost reduction

Based on results, profit and the company’s ROI. In short, the use of Big Data Analytics allows better performance and lower costs.

  1. New products and services

The most interesting use of big data analytics is certainly creating new products and services for customers. Online businesses have done this for many years; now with big data analytics, even large offline businesses are getting into this industry aiming an ever more complete offer towards their customers and their satisfaction.

To analyse Big Data, Microsoft recommends the use of Power BI for Office 365, a program that works as a suite for business analytics tools, with the objective of analysing data and sharing information. This tool can monitor the company’s activity and answer quickly with rich dashboards available on any device.

In general, we are in front of an analytic solution involving any organisation willing to control its activity through interactive reports. If you want to know more about Power BI, just ask for it!

The challenge of Big Data Analytics is the use of this data for achieving new business goals, that before were impossible to reach. A few years later and thanks to technological advances this quantitative change we’ve faced has also led to a qualitative change.

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