2024 is heading into its final stretch, and it’s natural now to try to figure out what trends will support the stock markets going forward. One key factor that we can’t ignore is the continuing boom in artificial intelligence.
Advances in AI technology have boosted the tech sector generally – but those gains have been especially strong in AI-related stock segments such as semiconductor chips, data center services, and data storage.
The last in particular deserves a closer look. Data is a main beneficiary of AI technology – AI requires enormous amounts of data storage to support even basic machine learning applications, and data center and server stack providers have been seeing a surge as AI has expanded. And this is opening up opportunities for tech-minded investors.
Covering the data sector for Oppenheimer, analyst Param Singh is flashing ‘Buy’ signals on two specific data storage stocks. We’ve used the TipRanks database to find out what the rest of the Street has to say about his picks. Let’s take a closer look.
Pure Storage (PSTG)
First on the list is Pure Storage, a company which, as its name suggests, is a specialist in data storage technology. Pure Storage offers what it describes as ‘simple and sustainable’ solutions for data storage, relevant and scalable to nearly any application. The key to the company’s success is giving customers a single platform for all their data storage needs, with a unified infrastructure – at a time when computer systems are fragmented, and not always compatible with each other, this presents a huge advantage.
In addition, Pure Storage’s data platform is designed to grow along with the customer’s business. The company has made data storage available with the popular as-a-Service subscription model, allowing users to have greater control over their budget, their data capabilities, and even their operating costs and energy bills.
In addition to its subscription service, Pure Storage also offers top-quality lines of data storage memory chips and flash storage arrays, designed to offer efficient…
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