If you are feeling overwhelmed by data, you’re not alone. For the past few years, businesses have been drowning in data. As technology and social media platforms make collecting and sharing data easy, the amount of user-generated content has exploded. Moreover, as businesses inevitably capture, analyze, and act upon data in real-time, more data is collected.
As a result of these digital trends, companies now have troves of datasets. What can they do with these immense sets of data? This is where the data analytics field comes into the picture. Analyzing raw data from sources such as sensors or social media posts to find valuable insights is not a new concept, but it is evolving with business operations as software makes it easier for companies to analyze vast amounts of data within shorter periods.
That’s why more and more students are signing up for everything from a Bachelor’s in Business to an online MBA in data analytics at schools such as Walsh University. Moreover, people in the field are returning to school because it’s vital to have the best skills to navigate the enormity of data for businesses. In other words, leaders need to learn to go beyond merely collecting data; they need to interpret it for action.
What is data analytics?
Data analytics is the process of extracting information from raw data. That raw data can be anything from sensors and social media posts to customer interactions. The aim is to find valuable insights. The process is typically automated and relies primarily on machine learning and AI, but it also involves human experts to evaluate the data. Moreover, experts within the field of data analytics try to make sense of unstructured data, which is data that hasn’t yet gotten into structured workflows. Much of that data comes in text, but it can also be gathered from videos, audio, and images.
You can apply algorithms to any data, including sensor data, social media data, or data from business systems. The most common uses for data analytics are fraud prevention, marketing and sales, and operational efficiency. For example, analyzing sensor data from a store could detect when someone placed something in a bag without paying. In marketing, you can get data insights using platforms that integrate social media and CRM analytics.
Why is it essential for business growth?
Using data analytics gives businesses the ability to find new revenue streams, increase customer retention and boost efficiency. In the past, businesses relied on data scientists to extract valuable insights, and that meant hiring specialists. However, technology has advanced, and now people with MBAs can understand how to use data to inform their company decisions properly.
With a better understanding of data, executives can now make sense of it much easier. In addition, many companies have a team of data engineers tasked with transforming the data into consumable formats. With these improvements, companies can now take advantage of the data that was once just sitting in databases.
The benefits of using natural data analytics
Data analytics can help businesses find unique opportunities. For example, you can use data analytics to learn to develop new products or optimize service operations. In short, by looking at trends and patterns that would otherwise go unnoticed, you have much more critical information at hand. Data analytics is also a cost-effective way for companies to increase revenue.
By automating data collection and finding insights, businesses free up employees to handle more complex tasks, which can reduce operational costs. Moreover, data analytics can help companies to increase customer satisfaction. Companies can find ways to improve the user experience by analyzing how users interact with their products. Data analytics can also help businesses enhance employee motivation and retention through gamification. By tracking the activities of employees, companies can provide incentives such as prizes or points to redeem for rewards.
Additional benefits of data analytics include:
- More accurate operational planning: Companies that use data analytics can spot patterns in their data and make more accurate decisions. For example, if there are changes to consumer patterns, it will be detected sooner.
- Improved customer service: Data analytics enhances customer service through the use of predictive algorithms. With predictive algorithms, customers don’t need to wait for staff to answer their questions. Bots can provide answers with human-like responses based on historical data.
- More accurate marketing and sales strategies: Data analytics is also effective in boosting marketing and sales efforts because the algorithms can detect patterns in data and make marketing or sales decisions on their own to provide more accurate and timely results.
How to start with data analytics
You might believe that getting started in data analytics is a major undertaking. Although data analytics requires understanding statistics and data visualization, technology is constantly improving, and that means that it gets easier for non-data scientists and engineers to understand dashboard information compiled from data. Moreover, some tools continue to make it easier for business leaders to get on board the data and knowledge revolution.
Some of the tools that can prove useful include:
- Extract, Transform, and Load (ETL) tools: These tools help extract data from various sources and transform it into a format that data analytics algorithms can consume.
- Data lakes: These platforms act as a central hub for data storage, helping to manage the transformation and loading of data into the data analytics platforms.
- Natural Language Processing (NLP): Businesses now use artificial intelligence trained in natural language processing to understand text such as emails and social media posts.
- Predictive analytics: Predictive analytics tools are highly effective in data analytics because they can spot patterns and behaviors and predict what leads and customers will do.
Place-based profiling
Data analytics also helps identify customer experience problems. With traditional marketing and sales, companies rely on surveys to collect customer feedback, but this approach provides limited information about each customer’s experience.
With data analytics, businesses can now use place-based data such as geolocation to identify potential issues. This could entail integrating data collected from transaction systems, customer reviews, digital signage, or geolocation data. As a result, businesses using sophisticated data analytics better understand the customer experience.
They can then use this data to improve operations, gather customer feedback and improve customer service. Data analytics can teach businesses a lot about their customers by investigating their location and actions so they can make the customer experience more personalized. This type of personalization is known as place-based profiling.
Companies can use geofencing technology to create virtual fences around buildings or other physical landmarks. Geofencing and place-based profiling allow companies to share offerings that make sense at that moment with customers. For example, at a museum event, it may entail sending a text message about a special sale taking place that day in the museum shop.
One of the best trends in business
Data analytics has emerged as one of the fastest-growing trends in business. This type of analytics has been around for a while, but in recent years, it has really come into its own. Data analytics is beneficial for businesses in many ways. It can be used for fraud prevention, marketing and sales, and operational efficiency. Moreover, the right tools and education can help businesses automate data extraction and synthesize it to make more insightful and strategic decisions.
Data analytics is a cost-effective way for companies to increase revenue. By automating data collection and finding insights, employees have more time to handle more complex tasks. It can also help companies to find unique opportunities they might have otherwise missed, plan new products for customers or determine how to optimize operations better. All of this happens in ways that were impossible before modern-day data analytics.
Fortunately, tools exist in the marketplace that helps businesses to increase customer satisfaction. As a result, executives can now spot trends and patterns that would otherwise go unnoticed with the right tools and companies can find ways to improve the user experience by analyzing how users interact with their products. This is especially important for customer satisfaction and retention.
Data analytics is one of the most essential components of modern business operations. The more data you have, the more insights you can glean from it and the better your decisions will be. Data-driven companies are better positioned to conduct business, innovate, deliver customer value, achieve strategic goals, improve customer service, and find new insights to grow and expand. There is no denying that data analytics has become fundamental in the modern business world.
