Data analytics has proven to be one of the most valuable tools in today’s business world. Getting into data analytics can seem daunting, especially when gathering and analyzing large amounts of information from disparate sources. 

Taking advantage of your data analytics program can be difficult without the right strategy. However, you can make much better choices using data analytics as your guide and not just your raw data source.

Upgrade to real-time

Real-time data analytics is a game-changer for businesses. It allows you to make decisions based on the most up-to-date information, which can help you improve efficiency and effectiveness. 

Plus, it can help you spot trends as they happen so that you can adjust your strategy on the fly. Businesses may take better action based on their data insights with the help of real-time data solutions like Striim real-time analytics. 

With this platform, business owners can explore patterns in customer behavior over time while making business decisions in real-time.

Use machine learning to uncover patterns in your data

Machine learning refers to algorithms that can make predictions based on data-learned patterns. For example, you might train a machine-learning algorithm to spot fraudulent activity by looking for habits in customer transactions.

The more information the algorithm has about what constitutes fraud and what doesn’t, the better it will be at spotting suspicious behavior. When used correctly, machine learning can help you improve your customer retention rates and increase productivity.

Incorporate accurate, externally sourced data

Externally sourced data can be a great way to supplement your data and improve your analytics. However, ensuring that your data is accurate and up-to-date is essential since inaccurate or outdated data could provide a false representation.

Additionally, incorporating external data with your own ensures that you have all relevant information necessary for making decisions on behalf of your company.

For example, looking at customer feedback from social media sites may not be enough to review recent posts. Studying more historical posts will give you a better understanding of what customers say over time rather than just within the last few days.

Monitor the quality of your data

Data quality is a vital component of making data analytics work. Data quality has three dimensions comprising accuracy, timeliness, and completeness.

Monitoring the quality of your data is essential to using your analyses properly. When you find an issue with one of these three dimensions, you should fix it promptly to avoid inaccuracies in the rest of your dataset. 

One way to monitor this is by using dashboards. They allow you to see all aspects of your datasets simultaneously so that there are no surprises later on when performing analysis.

Visually represent the data

When handling data analytics, visualization is a great way to communicate findings and help people understand what’s going on with their business. You can visualize your data in various ways, including line graphs, bar graphs, pie charts, scatter plots, bubble charts, and timelines. 

Choose one or two visualization types that work best for your business and use them consistently throughout your analysis. They can impact how your audience views your insights and findings. 

By representing your data visually, you can more easily see patterns and correlations that would be difficult to spot otherwise. It can help you make better decisions about your business and operations.

Invest in data interoperability

Data interoperability refers to the capacity of two data sources or tools to exchange information. There are many cases where a data source can have missing or inconsistent data that you could correct by merging it with another, complete data source. 

For example, you may need access to customer transaction records and surveys to generate reports on how customers shop at your store. In this case, both data sets should come from the same point in time to be comparable. 

You can invest in data interoperability to make the most of your data analytics. That means ensuring that your data can be easily accessed, processed, and analyzed by the right people.

Look at correlations across multiple metrics

Data analytics involves numerous metrics and dimensions. An excellent way to make sense of all these data points is by viewing correlations across multiple metrics. 

That way, you can better understand how each variable affects another. Look for patterns and trends in your data to find out what might be causing them, and use this information as part of your decision-making process. 

Analyze which changes seem to lead to good outcomes and try replicating them. Remember that not every change leads to positive results, so always look for negative correlations.

Before you go

Data analytics are a vital component in the success of any business. Getting the most out of your data analytics starts with setting goals, then understanding where your organization stands before applying different analytics types.

Kenneth

Kenneth is a proud native of sydney, born and raised there. However, he pursued his education abroad and studied in Australia. Kenneth has worked as a journalist for almost a decade, making valuable contributions to prominent publications such as Yahoo News and The Verge. Currently, he serves as a journalist for The Hear Up, where he focuses on covering climate and science news. You can reach Kenneth at [email protected].