SolarWinds Executive Believes AI Can Solve Data Management Problems

CNME Editor-in-Chief Mark Forker spoke with Sascha Giese, Head Geek at SolarWinds, to find out why he thinks implementing AI and machine learning can help businesses manage their data and become more secure, despite resistance from some over the use and cost of the technology.

Sascha Giese, Head Geek, SolarWinds

Giese is a highly respected figure within the IT community and SolarWinds is a global leader when it comes to equipping businesses with the solutions and tools needed to effectively manage their IT infrastructure and environments.

We know that over the past 18 months, there have been seismic shifts in the IT landscape, not just in the Middle East, but around the world – as a direct result of the COVID-19 pandemic. However, as we have now adapted to the complexities of our current climate, the question now is, what will the future look like over the next 12 months?

We know that data volumes have grown exponentially and this trend is expected to grow exponentially over the next 3-5 years. However, as many companies struggle to get a handle on managing their data volume, we asked Giese what he thinks companies need to do to better manage their data.

“There are many different strategies companies can adopt to better manage their data volume, but it all depends on their budget. For many companies, there is still a lot of uncertainty about the future due to the ongoing pandemic issues, which has resulted in many budgets being cut significantly. Some companies try to be as cost-neutral as possible and embrace data operations theories, which allows you to merge different teams working together to better manage the massive amount of data collected, making it easier to a data company. consumer to engage with its tools and solutions, and it usually comes at no cost. The other way to manage your data could be implementing AI and machine learning,” Giese said.

While Giese is a strong advocate for implementing AI in IT infrastructure and business operations, he admits the technology comes at a cost, however, he believes businesses should adopt it to be on the safe side. able to meet the challenges they face in the digital economy.

“Basically it’s a calculation, but you need to figure out how many people you need for a specific task and consider how much it costs. For example, data analysts are not cheap and if you need 30-50 every year, how much does it cost you as a business? On the other hand, you might have a machine learning or AI system which, again, isn’t cheap, but at some point there’s this break-even point, where the math goes in one direction and at that point it makes sense to start down the path of implementing AI,” Giese said.

A report recently commissioned by Gartner indicated that more and more governments are spending on AI, but in Europe there remains a high level of skepticism among the workforce regarding the integration of AI in daily operations. Giese believes that the main difference in attitudes between the two markets is that the Middle East is more “open”.

“I think the Middle East is a bit more open because the whole subject of IT is much younger compared to Europe. If you think about automation, there was huge resistance to it from network admins because people thought it was going to take their jobs, and there were trust issues about what the script was doing because that they had not written it themselves. 5% of AIs are self-written, and everything else is bought off the shelf, so you never know who created these things, so there’s a huge trust issue. There’s a famous saying that if I want to do something good, I’m going to have to do it myself and I think that mindset applies to a lot of IT personnel when it comes to AI,” said Giese.

Security is a huge challenge in the IT ecosystem, and Giese advocated for the introduction of AI to enable businesses to be better protected against cyber threats.

“We know that large teams in a security operations center are tasked with managing huge amounts of data and they need to compare all that data to make sense of it, now we know humans can do that, but they can’t do it as fast as a machine. A machine can understand thousands of different performance indicators and metrics in a much shorter period of time. Machine learning basically means that someone was teaching something thing to a machine, so we’re basically telling a machine if this and that happens to do that, and that creates an if and then scenario If something happens, a machine is much faster in terms of applying actions you or I, or any security analyst There are many, many use cases for AI, but implementing it into your operations is key to strengthening your security. é,” said Giese.

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