Today, every organization has more data than ever at its disposal. But deriving meaningful insights from it to improve operational efficiency remains a potent challenge. Data Analytics appears to be a practical solution for this problem.
What is Data Analytics
Data Analytics refers to the process of examining copious amounts of Big Data to uncover hidden patterns, correlations and other insights with the aid of specialized systems and software.
It is a trending practice that many companies are embracing and adopting to gain competitive advantages over business rivals and drive new revenue. However, it is first essential to first understand its landscape (types, challenges, and opportunities) before putting it into the application.
From a market perspective, it’s necessary to choose the right type of Data Analytics tools for data analysis.
Data Analytics Tools can be distinguished into 2 basic types:
- Simple Data analytics
Mainly focuses on the description of an event that has already occurred, finding its root causes and offering insights.
- Complex Data Analytics
it can be further sub-categorized into
- Predictive Modelling – data collected is mined for patterns indicative of future situations and behaviors.
- Prescriptive Modelling – subsumes the results of predictive analytics to suggest a corrected course of action that can take advantage of the predicted scenarios.
Depending on the appetite for Data Analysis of your organization, you can consider any of the above data Data Analytics application to handle large volumes of data, improve its operational efficiency and drive new revenue.
What is Data Analytics used for
Even the simple products sometimes have very complex potential problems and so different permutations/working solutions via Data analytics need to be incorporated to quickly resolve the situation. Other potential benefits include,
Faster and better decision-making
With the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned.
Cloud-based analytics bring significant cost advantages. It helps in identifying more efficient ways of doing business rather than relying on archaic trial and error experience.
New products and services
With the ability to gauge customer needs and satisfaction through analytics, more companies are now in a position to develop new products to meet customers’ needs.
Curbing money laundering menace
Money laundering risks have grown in complexity and scale in recent years. Data analytics has proved of immense help in detecting and pursuing transnational crime and money laundering, thereby strengthen regulatory framework enforcement approach.
Hope this gives you some basic idea of Data Analytics is all about.