​​Modern businesses create a ton of incredibly valuable ​data that companies use to inform business decisions. ​But before ​organizations​ can put ​data​ to good use, it needs to be collected and formatted correctly. ​     ​​ 

​​There’s a high demand for Data Scientists and Analysts ​who​ know how to find actionable insights in massive datasets. Smart devices, for example, generate machine data, which is ​challenging​ to decipher because ​it’s not formatted​ ​and there’s simply so much of it​. That’s why we use big data analytics tools like Splunk that make it easier to find variations and patterns in data. 

Splunk is a cloud-based platform designed for big data analysis. It’s great for working with high volumes of incoming unstructured data, power automation, and machine learning.

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What is Splunk used for? 

Splunk is used to power through machine-generated data and reveal the insights within. Instead of dealing with a high volume of unformatted data, Data Analysts can use Splunk to format it and make it easier to find ways to improve operations. From there, they can use AI to predict and forecast traffic, find abnormalities in incoming traffic patterns, and build full data models. Ultimately, this all helps make data more user-friendly and easier to understand. 

Splunk can collect data from a range of sources, allowing you to analyze the results of all your efforts in one place. This prevents data siloing (when data is stored in isolation from the rest of the organization), ​which tends to be​ common in larger organizations. It also helps reveal more detailed insights by consolidating data from all sources.  

Splunk uses a three-stage data pipeline

  • In stage 1, data is collected from the source and formatted to include the metadata keys needed to make the next stages possible. 
  • In stage 2, Splunk parses data, sorting it into individual events based on the timestamp and adding metadata keys to these events. Event data then transforms based on the rules you define. 
  • In stage 3, these parsed events are transferred to a disk with an index file attached to allow fast search across all the data. 

The data gets compressed so that it only takes up 15% of the original storage space and is stored in what’s known as file buckets. These buckets can identify whether the data is composed of letters or numbers and sort them accordingly. With the data sorted, you can then search through it,  or use it to create reports and dashboards, or generate pivot reports that can be displayed as visualizations like tables or charts

Spunk also allows you to process data in real-time. Cleaning and formatting data happens instantaneously, keeping the data current as you look at it. This prevents the lag times seen in some data processing platforms and makes it easier to find issues or outliers when they occur. 

By looking at real-time data to monitor the devices that make up your network, you can minimize any downtime coming from an issue with a broken component. And while Splunk is mainly used for data-related tasks, it also offers cybersecurity solutions. Unifying security operations and monitoring them through Splunk for Security makes it easy to detect outliers and protect data stored in the cloud. 

Who uses Splunk? 

Splunk is a versatile tool with a ton of applications, so all sorts of teams use it. For example: 

  • Security: Introducing automation into data protection allows security professionals to make decisions without getting lost in the numbers. 
  • IT: Splunk helps reduce downtime and outages, allowing IT to monitor KPIs from a range of sources to quickly identify any issues and fix them. 
  • DevOps: Full-stack observability allows DevOps to unify data and set metrics, then monitor the progress they’ve made. 
  • Management: Thanks to the software’s easy-to-understand dashboards, users with little understanding of raw machine data can use Splunk to get a high-level view of what’s happening across the enterprise. 

Other uses for Splunk 

​​S​everal big name ​companies​ on the Fortune 100 list​ use Splunk​, including ​organizations​ in finance, healthcare, social media, and retail sales. Splunk’s real-world applications show how you can use data to power insights that impact people’s lives. 

Health and medical organizations can use the machine data generated by patient-worn sensors to monitor the overall health of a hospital ward and be alerted to any variations in the data. When a change in data appears, healthcare professionals can ​use Splunk to ​investigate data changes and promptly respond with specialized care if needed. 

Splunk is great for companies using Hadoop to track and store machine data. As the Hadoop framework ages, it can be time-consuming or even impossible for enterprises to extract the necessary insights from this program. Splunk Hunk integrates with Hadoop to make visualizations that are traditionally not possible with Hadoop-based datasets. The Splunk virtual index separates data storage, making analysis and dashboard creation simpler. Like Splunk’s cloud platform, Splunk Hunk handles unstructured data without manual formatting, which is valuable for Hadoop users dealing with a lot of raw data. 

Splunk architecture 

Splunk architecture follows the structure laid out below, with key components acting to process data: 

  • First, the Splunk forwarder collects data from files and scripts through the universal forwarder component that collect data to send to the indexer. You can install this component on the client’s side or within the application server. Splunk also has a heavyweight forwarder that offers advanced functionality to parse data as it’s being collected. 
  • Next, Splunk’s indexer processes data if necessary or receives the forwarded data and stores it in file buckets until it needs to be deployed. The file buckets compress and store the data. User access and controls are managed at this level, with each indexer having its own rules and boundaries. With the data organized, the indexer can also search through the numbers. 
  • The Splunk deployer manages any search heads and indexers used during deployment. The deployer can host and deploy apps or technology add-ons wherever they need to within the Splunk infrastructure. 
  • The search head produces dashboards and visualizations that end users see when interacting with Splunk. It allows users to search the data and generate reports with the results. 

Splunk also has a built-in license server that monitors usage. 

Learn more about data analysis 

Knowing how to use data to help a company achieve its goals is a powerful skill that can open the door to many professional opportunities. If you want to learn more, check out our data analytics courses like Introduction to Big Data with PySpark.

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