Is Microsoft (MSFT) the Best Big Data Stock to Buy According to Analysts?

We recently published a list of 13 Best Big Data Stocks to Buy According to Analysts. In this article, we are going to take a look at where Microsoft Corporation (NASDAQ:MSFT) stands against other best big data stocks to buy according to analysts.

The big data companies focus on collecting, storing, and analyzing huge amounts of data that businesses use to make smarter decisions. This data comes from many sources, like websites, sensors, social media, and customer interactions. These companies aim to find patterns, trends, and insights that help companies improve various aspects of their business, including their products, services, and operations. Key areas within the industry include data storage, analytics, cloud computing, and AI-driven solutions.

As companies increasingly rely on data to optimize their processes and predict trends, industries like healthcare, finance, retail, and manufacturing are adopting big data solutions. The industry is growing rapidly, driven by technological advancements, especially AI, machine learning, and cloud computing, which help process and analyze data more efficiently. Many companies are offering cloud-based big data solutions, enabling businesses to access powerful data storage, processing, and analytics tools without the need to maintain expensive on-premises infrastructure.

Big Data Stocks are Poised to Grow

As businesses turn to AI and automation, investors are piling on to big data companies that offer AI-driven analytics platforms. Companies focusing on real-time data processing and analytics are also attracting investor attention, given the growing need for businesses to make quick decisions based on live data. The global big data market size was valued at  $327.26 billion in 2023 and is projected to grow at a CAGR of 14.9% from 2024 to 2030, according to Grand View Research.

Here are some ways big data stocks are likely to benefit. The amount of data generated globally is increasing rapidly due to more connected devices, social media, sensors, and IoT (Internet of Things). This creates a growing need for companies that can collect, store, and analyze vast amounts of data efficiently. Meanwhile, the shift to cloud computing has made it easier for businesses to store and process big data without investing in expensive infrastructure. Cloud-based big data solutions are scalable, cost-effective, and flexible, making them an attractive option to companies of all sizes. Big data companies are closely tied to AI and machine learning, which require vast amounts of data to train algorithms and generate insights. As AI adoption grows, so does the need for platforms that can manage and analyze large datasets.

Our Methodology

To compile the list of best data stocks to buy, we reviewed Big Data ETFs to compile a preliminary list of stocks and then selected the ones with the highest upside potential, based on Wall Street analysts’ average price targets. We have also mentioned the hedge fund sentiment around each stock, as of Q4 2024.

Note: All data was recorded on April 7, 2025.

At Insider Monkey we are obsessed with the stocks that hedge funds pile into. The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 373.4% since May 2014, beating its benchmark by 218 percentage points (see more details here).

Is Microsoft Corporation (MSFT) the Best Big Data Stock to Buy According to Analysts?

A development team working together to create the next version of Windows.

Microsoft Corporation (NASDAQ:MSFT)

Upside Potential: 39.72%

Number of Hedge Fund Holders: 317

Microsoft Corporation (NASDAQ:MSFT) is a significant player in the big data space because of its comprehensive offerings and role in the broader data ecosystem. Microsoft’s Azure is one of the leading cloud computing platforms, and it plays a major role in big data analytics. Azure provides a variety of tools and services that help organizations store, process, and analyze vast amounts of data. The tech giant’s Power BI is a business analytics tool that helps organizations visualize and share insights from their data. It can connect to a wide variety of data sources, including big data platforms, and is used to analyze and make sense of large datasets.

Microsoft Corporation (NASDAQ:MSFT) posted a revenue of $69.6 billion, up 12% year-over-year for the second quarter of its fiscal year 2025, driven by Azure. Revenue from the cloud platform hit $40.9 billion, a 21% increase year-over-year. However, over the past six months, the company has canceled data center projects totaling 2 gigawatts of electricity capacity in the U.S. and Europe, according to a report by Bloomberg. This decision stems from an oversupply of data center capacity relative to its demand forecasts, leading to a reduction in support for additional training workloads from partners like OpenAI. That said, Azure is likely to continue to grow. The rise of IoT and real-time data processing is pushing demand for edge computing, and Azure is investing in this area. Azure’s Edge services, combined with AI and machine learning at the edge, are allowing businesses to process data closer to where it’s generated, improving latency and efficiency.

Overall, MSFT ranks 10th on our list of best big data stocks to buy according to analysts. While we acknowledge the growth potential of MSFT, our conviction lies in the belief that AI stocks hold great promise for delivering high returns and doing so within a shorter time frame. There is an AI stock that went up since the beginning of 2025, while popular AI stocks lost around 25%. If you are looking for an AI stock that is more promising than MSFT but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock.

READ NEXT: 20 Best AI Stocks To Buy Now and 30 Best Stocks to Buy Now According to Billionaires.

Disclosure: None. This article is originally published at Insider Monkey.