Relevant & Advanced Data and Analytics.
Lumos Consulting provides efficient network analytics services for your business, creating a more dependable and powerful process.
A network is one of the most important parts of the company’s operations. It’s used to transmit data across the entire company so it needs to be always efficient. Since it generates a lot of data that needs to be analyzed, it leads to the creation of network analytics.
Network analytics is the study of network data to identify different trends happening in your network. Since networks constantly grow in size and intricacy, IT departments have to access insights and trends to make sure the network operates smoothly.
Proper solutions and tools should be used to successfully perform network analytics. Here is a rundown on the importance of data analytics automation:
Overview of Analytics and Automation Software
Automation can speed up data analytics. A data scientist will perform efficiently with the help of computers that can complete processes that are more complex for humans. Your business can also save more time and money as these machines can execute analytics accurately and efficiently.
Here are some things that can require data analytics automation:
- Dashboards and reporting. Automated data analytics systems can process data for publishing to live data summaries.
- Modifying a data warehouse. Your business can use tools that automatically integrate new data or migrate data from legacy systems.
- Data preparation tasks. Tools like KNIME can label data and repeat study runs to optimize parameters.
What is Endpoint Analytics?
Endpoint analytics provides insights on the performance of your organization and the quality of experience your users receive. It can also help identify hardware issues that might cause devices to slow down and help you make improvements beforehand.
It collates and analyzes data to make an endpoint profile, then applies artificial intelligence techniques. It is beneficial in determining whether devices pose a security threat. Here are the steps on how endpoint analytics work:
- Data collection. A complete set of data is essential in building a complete profile for every endpoint. Some information sources are Deep Packet Inspection (DPI), telemetry information and asset information.
- Data analysis. The collected data will show important details about endpoints like models or operating systems.
- AI/ML and crowdsourcing. When the endpoints can’t be easily identified, Artificial Intelligence (AI) and Machine Learning (ML) techniques will combine the collected data and use an algorithm to group them according to common attributes.
- Grouping. Endpoint analytics will categorize the newly profiled endpoints into groups. This is for easier application of security and Quality-of-Service (QoS) policies.
DNA Analytics and Assurance
Data center analytics use a lot of platforms to facilitate the simultaneous use of multiple data sources, data collection methods and presentation techniques.
These platforms can include machine learning and advanced analytics technologies to improve data center operations like network assurance, intelligent troubleshooting or IT ticket management.
With proper network visibility, you can manage all of your devices and services, identify and solve issues ahead of time and guarantee a better user experience on all networks. You can also efficiently grow your network and enhance performance but still be able to save more time.
A network is one of the most important parts of the company’s operations. It’s used to transmit data across the entire company so it needs to be always efficient. Since it generates a lot of data that needs to be analyzed, it leads to the creation of network analytics.
