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Log Analytics simplifies enterprise tech support

Enterprise technical support engineers make life easier for business users, product users and employees in an organisation who badly require technical support. An enterprise technical support employee monitors and maintains the computer systems and networks within an organisation.

He is the first person anyone will approach when they have technical issues with the enterprise products such as product malfunction, installation and configuration of systems, diagnosing virus attacks, hardware, software issues, and solving technical problems for the enterprise.

Any business cannot afford to have faulty workstations for more than a minimum time taken to repair or replace them. Enterprise tech support is vital for a superior operational efficiency of the enterprise. These tech support engineers would work for a software or equipment suppliers and provide post-sales support either in-house or for companies that specialises in providing enterprise tech support.

Log analytics, data logging, data analysis

The typical process that is followed by a technical support engineer is check for tickets. When a ticket is raised, the engineer opens the ticket and analyses the log data. Analysing these log data is a time consuming process because understanding the issue from a log involves manual effort and intervention.

Once the issue is identified, the support engineer troubleshoots the problem. As this process is time consuming enterprises started hunting for an automated log analysing process that will automate the whole log analysis process and the answer to this quest is the birth of "Log Analytics"

Log Analytics brings in three benefits to the enterprise.

  1. It helps the enterprise in saving time and cost
  2. It helps in product enhancement
  3. It delivers superior customer experience

1. Time and cost saving

Log analytics software engine decodes the log data and converts them into meaningful information. When the customer uploads a log through a particular device, a log will be created. When the tech support engineer opens the log data through this engine, he will see a decoded insightful information which will enlist the problems, available fixes and versions that could solve the problem. The engine also lists out the details of other customers who are affected with similar issues.

This automated process enables helps the trouble shooting to happen in a jiffy and it saves a lot of time. The traditional way of decoding log data through ASCII and hexadecimal values will be replaced by log analytics which will be majorly useful for tech support to reduce time in issue resolution. This in turn saves cost.

2. Product enhancement

Log analytics not just identifies the problem in a single product but also gives details about other products that has a similar problem. This helps the product team to identify which feature in the product needs more attention.

Log analytics gives the configuration data like which feature is predominantly used. Say for example – VPN, if VPN is used predominantly, that acts as a good data point for R and D to focus on to enhance the product features.

3. Superior customer experience

By monitoring everything from customer transactions to security events and network activity, Log analytic engines helps the tech support engineer to gain valuable operational intelligence from the machine-generated data. The tech support engineer is aided with insights, use-cases and visuals that help them in solving customer issues in less time.

When the customer gets speedy issue resolution, has access to an enhanced product he becomes a delighted customer. Such a customer becomes an evangelist for the enterprise. It is a pure win-win situation in which the enterprise saves cost and the customer is happy.

The enterprises that will move ahead of the rest in the enterprise tech support market will be the ones that have log analytics engine in their armoury. Do you have log analytics engine for your tech support organisation?

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