Thursday, November 11th, 2021

Big data contains an extensive variety of analytics and data-gathering methods. It is data management, often with an aim to draw out and understand business insights, but it’s all about volume.

Fundamentally, it refers to the capacity to record, store and analyse data on a massive scale. Big data follows this basic thinking: the more we know about the challenges at hand, the more chances that the solution will be precise and reliable.

Big data, by nature, comes embedded with enormous data sets that can be studied. This helps with uncovering patterns and associations, especially when it comes to human interactions and behaviour. For example, a business with a strong system to understand their data will likely enjoy the advantage of distributing tailored recommendations to boost sales.

The data revolution continues to mature, thanks to the growth of the Internet, social media, smartphones and other smart devices, social media and other technology.

What is big data?

Big Data is a collection of enormous data and continues to grow (exponentially) with time. It’s a type of data so vast and complex that no traditional data management tools can store it or process it efficiently.

What are augmented analytics?

Augmented analytics are the use of technologies such as machine learning, artificial intelligence and natural language processing (example: mobile personal assistants, such as Siri oniPhone) to assist with data preparation, creating insights and presenting them in a way that complements the way people explore, analyse and use data.

Augmented analytics, instead of replacing human beings, enhances our interpretation skills. This helps when working with large and complex data sets, and it facilitates the creation of business insights directly from the data at your disposal.

As a business thinking about investing in big data and augmented analytics, below are some of the benefits of finding new ways of managing an increasing volume of data and generating insight from analytics.

  • Faster decision-making

Augmented analytics can easily recommend which data sets to include in analyses, alert users when datasets are updated, and suggest new data sets when users do not receive the expected results.

The process of decision-making becomes easier to track and manage with the organisation.

  • Customer acquisition and retention

To win, businesses need to have unique strategies to market products. Through the usage of big data, it becomes easier to pinpoint precisely what customers are seeking to purchase.

Through data and analytics, it’s easier to establish a solid customer base straight from launch because communication is targeted and with time, easily anticipated.

Big data processes perceive the patterns of consumers; they use the patterns to generate brand loyalty by collecting more data to identify more trends and ways to anticipate customers’ needs and meet them efficiently.

  • Potential Risk Identification

In a digital world, businesses work in high-risk environments. The environment requires savvy data and risk management processes.

Big data can improve the effectiveness of risk management models and create smarter (near-real time) strategies.

Data needs to be of high quality and well managed before it can be reliably analysed.

With data constantly running through the organization, it’s essential to establish processes for the maintenance of data quality. When the data is reliable, the next step is to establish a master data management program that places the entire enterprise on the same page with real-time data flow.

Big data is a budding field that offers enterprise-level businesses the resources to make critical and informed business decisions. It’s also an opportunity for businesses to be more systematic in the way they analyze and see the world.

At Quarphix, we handle and store data for businesses and organisations of different sizes. We offer 24/7 Servers MonitoringQuick Data Restoration, and a flexible yet robust IT environment for your cloud/data hosting requirements.

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