Solving Data Quality Challenges with Strong Data Management Strategies

[Hodor]

Hi there,

I'm having weird behaviours with Insigfht Remote Support server. I've been adding physical host to it without any issue for a while, but not for the last two servers I added.

I connected one physical server with ESXi (let's call it esxora23) to IRS, then I inserted iLO credentials in IRS and clicked 'discover', and then IRS server changed the hostname to DC38, which exists in my pool but it's not even physical and it's in a separate hypervisor and in a different network,

Same behaviour when adding esxora24 to IRS, and now I have two servers called DC38. Funny fact is that they are passing all checks and they show up green in IRS frontend.

I've checked reverse dns, and it's ok. MAC addresses are also different, of course serials also differ, and all hostname fields in iLO setup are fine. Hosts file in IRS server is blank.

I can't figure out what's going on, would you please lend a hand on me?

Regards

[Hodor · Accepted solution]

Ok, i found the problem... sadly, my fault

I just typed the domain instead of the full fqdn, in fqdn/ip field   xDDD   ... things that happen when you register lots of servers

[Sunitha_Mod]

Hello @Hodor,

Great! 

We are glad to know you were able to resolve the issue and we appreciate you for keeping us updated. 

[missmakimachain]

Organizations often struggle with maintaining high-quality data due to issues like data silos, inconsistent formats, and duplicate or outdated records. These challenges can lead to poor decision-making and inefficiencies across departments. A strong data management strategy helps solve these problems through clear data governance, integration between systems, and master data management (MDM) practices. Data governance sets rules and accountability, while MDM ensures a single, accurate source of truth. Integration tools help unify data from different sources. Additionally, automation and AI can support by cleaning, validating, and monitoring data quality more efficiently. Together, these approaches ensure more reliable and usable data.