Data is king. The power that lies beneath the vast amounts of data that gets generated every second is beyond imagination. And the numbers don’t seem to slow down. On the contrary, they’re increasing exponentially.

Data collection and analysis will help you understand your customers and your product better. In short, they’ll transform your entire organization. The challenge is to collect and analyze data efficiently. That way, you can benefit from it the most.

In this post, you’ll find out about the most populous and most challenging-to-handle type of data: machine data. You’ll see what makes machine data valuable and why it’s important to collect. Finally, we’ll cover how to make the most out of machine data by using powerful tools.

Machine signifying machine data

What Is Machine Data?

Machine data is by far the largest source of big data and the most complex. It’s been estimated that the majority of the world’s data is generated from machines. For example, let’s say you turn on your GPS to help you find your destination. Or you use that fancy robot cleaner to tidy up your house while you’re gone. In either case, probably without realizing it, you’ve generated a tremendous amount of data.

Also, machine data is complex because it can only be interpreted and understood by other machines. That’s because of its lack of structure. In other words, this type of data has no significant business value—unless it’s properly deciphered.

What devices are generating all this machine data every second?

  • Computers
  • Mobile phones
  • Embedded systems
  • Sensors of any kind
  • Web and network logs
  • Many other sources

The widespread availability of smart devices and their interconnectivity, known as the Internet of Things (IoT), has vastly increased the information available.

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Why Would You Want to Collect It?

Machine data is a great source of invaluable insights and business benefits. But for the most part, this source of data remains untapped. The most important facet is the application—in other words, how humans can gain value from this data.

All businesses need to understand their consumers’ collective behavior if they want to stay ahead of the competition. Companies can gain insight by using appropriate data products.

Machine data has tremendous potential to enable models with higher precision in many application areas. These models have the ability to change how businesses operate.

  • They can help create innovative approaches to how companies market themselves and sell products.
  • They can affect how companies manage human resources.
  • Also, they can change how people and organizations respond to disasters.

These models are useful in many other cases where people are making decisions based on substantial data amounts.

Listening to Each Consumer

More specifically, machine data allows you to hear the voice of each consumer as opposed to consumers in general. This adds a level of business insight that wasn’t imaginable before!

Imagine how companies can see the purchase histories of their potential customers. It’s possible to learn what their interests are. Recommendation engines use user patterns and product features to predict the best match product for enriching the user experience.

Improving Daily Operations

Naturally, you want to make sure that your customers receive the level of service they expect. For this reason, you must ensure critical processes are running according to their intended capabilities. By using real-time machine data delivery, you and your organization can improve the way you operate daily.

Pinpointing Issues Early

Also, by collecting machine data, you don’t have to worry about unexpected problems affecting your applications and network. Using this data correctly gives you the opportunity to detect problems early and allows you to solve them before they become tricky.

Cases Where Machine Data Is Useful

A wide range of companies use machine data to boost aspects of their operations. Below, we’ll take a small sampling of where and how you might use this powerful tool.

1. Log Management and Analysis

Many business applications rely heavily on log data. Logs contain time-stamped data on actions and decisions that applications have made. They include other runtime information as well.

Log management and analysis aren’t new concepts. But the amount of log data coming from business operations is always increasing. And as that happens, so does the challenge to store, analyze, and present the data in the most effective way possible.

Many tools offer log analysis and help you collect and analyze enormous amounts of log data without going through the process of dealing with relational databases. Log analytics applications address various business goals, including:

  • Cybersecurity
  • Systems maintenance
  • Analyzing market trends
  • Personalizing customer experience

Let’s talk a little more about that last point.

2. Personalizing Customer Experience

Any time a user interacts with an application, that user leaves a trail behind. And these trails are invaluable data for companies. Why? Because companies can adjust their products to better suit the customer experience.

By using log data, companies can predict user preferences. Then they can personalize their products—even in real time! And that often means an increase in conversion rates.

Also, log data generated from billions of clicks and user behavior patterns is the power behind a very popular feature, most commonly used in streaming services. That feature is real-time recommendations tailored to each user.

3. Improving Cybersecurity

Companies are constantly facing fraudulent activity. They use data analytics to detect patterns of fraud and irregularities within their systems.

Systems can examine massive amounts of log data. They use patterns in this data to identify and prevent potential fraudulent behavior. You can find this type of log data on all kinds of devices, databases, files, and applications.

Furthermore, companies using this data can find out about cybersecurity threats that their security systems haven’t even detected! This happens when a company combines data from internal and external sources.

4. System Preventive Maintenance

Organizations take advantage of machine-generated data to ensure their systems remain fully operational. For many industries, downtime can result in a significant loss of revenue. Data coming from systems, such as logs, sensor data, and IoT data, can provide an early indicator of failure. 

By using this data, companies can mitigate the negative results of unforeseen problems such as downtime, natural disasters, outages, and so on. And that leads to happier users and happier customers.

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How Data Analytics and Visualization Tools Can Help You

As the amount of data increases, so does the difficulty in taming it and making something useful out of it. Analyzing the data provides general insights and helps you identify opportunities in your current and prospective markets.

Also, these insightshelp you make changes that could set you ahead of the competition. Machine data, as mentioned earlier, is complex and mostly unstructured. Therefore, using top-notch data analytics tools is the best way to go.

To successfully implement analytics, have a thorough plan before you start. Consider what data you should collect and how you will measure it. This early planning will prove extremely useful.

Afterward, you can use analytics tools to analyze the data. Most likely, you’ll have access to real-time insights from across your organization. Real-time analytics can help your company improve collaboration within and between teams. And that leads to better results.

Visual Representation of the Analysis

Data visualization tools are great for making all the data meaningful to its users. In other words, you can present the analyzed data in a form that’s easy for others to wrap their heads around, such as graphs, charts, and images. This straightforward way to represent otherwise complex data allows humans to extract valuable insights from machine data.

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New Revenue, New Efficiencies, New Advantages

Through data analytics, you can drive new revenue, improve operational efficiencies, and gain a competitive advantage. But you must understand what you’re looking for out of your data! Once you’ve established that, you can use and benefit from a data analytics solution.

Scalyr allows you to ingest, store, and analyze vast amounts of data in real time. It can also significantly reduce your operational costs, and it offers lightning-fast query results. Contact Scalyr to find out the best solution for your business.

This post was written by Alex Doukas. Alex’s main area of expertise is web development and everything that comes along with it. He also has extensive knowledge of topics such as UX design, big data, social media marketing, and SEO techniques.

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