Big Data

What Is Data Analytics And Why Is It Important?

Whether your company is just starting or attempting to stay afloat during this trying time, it’s essential to put the necessary steps in place to keep growing. The best way to do that is to make good use of the data available.

Data analytics is essential for business growth as it allows companies to monitor and act on things like:

  • What’s working? 
  • What needs areas need to improve?
  • What do customers want?

Using up-to-date technologies and advanced processes, businesses across industry sectors can keep a competitive edge that allows them to scale. Here’s how.

1. Utilize artificial intelligence 

One of the major problems businesses face with data analysis is the sheer volume of information. Every day, each consumer generates an average of at least 1.7 megabytes of data, with that number continuing to rise. That’s far too much for even the most experienced human data analyst to handle alone. 

AI can evaluate massive data sets quickly and efficiently. With the power to learn from their findings as they analyze, AI programs can predict new trends and produce forecasts with impressive accuracy, all in a mere fraction of the time it would take a person.

With the help of the trends and predictions generated by AI programs, companies will be far better prepared to act on the numbers. They can also expect a greater degree of success when they put strategies in place by detailed analysis.

In addition to crunching the numbers, companies can also use AI programs to analyze data from different sources and compare it across platforms. They can also recommend possible actions related to consumer opinion data and use past data sets to respond to queries, meaning it’s never been easier to center customer experience.

2. Lower your risk

With data analysis, businesses can better manage and reduce their risk. And, it’s essential to do so, particularly in the wake of the past 18 months. As the economic recovery continues after the worst of the coronavirus crisis, companies have to do all they can to ensure the strategies they put in place will perform well. 

There are a few ways to do this using data, including break-even analysis, which allows companies to find the point at which the products they sell will start to profit. Break-even analysis offers an invaluable insight into how risky any given investment might be. With eyes on that sort of knowledge from the outset, companies can prepare at every stage of each new investment opportunity.

Another way data analysis can help with risk management is in helping to drive better, more informed decision-making at the very highest level of an enterprise. Considering stats around growth and performance will be far easier for goal-setting that is both ambitious and achievable. Budgeting efficiently will also be more straightforward for companies with an enhanced understanding of performance.   

3. Include data visualization

Data analysis can be a big job, even with advanced tools like AI.  As such, data visualization can be invaluable. 

In basic terms, data visualization means representing information regarding performance, sales, customer satisfaction, and more through charts, graphs, maps, infographics, and other graphic displays. Putting raw data sets down in visual formats like these makes it much more straightforward to spot patterns and find meaning. 

Not to mention the fact that making data visual can be a great way of providing helpful context. Say, for example, you wanted to use data analysis to push for a new high yield investment that you’re sure will drive revenue. While it would likely be challenging to communicate the benefits through raw data alone, a visual display can help to show:

  • What trends can you see?
  • How is that investment predicted to perform?
  • How risky is that investment expected to be?

In other words, data visualization has the power to take detailed stats and turn them into something easy to understand and actionable. Among other things, this makes it a powerful communication tool.  

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