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Materialize Announces Two Series Investments Totaling $40M 

On Monday, Materialize announced a $32M Series B round led by Kleiner Perkins with participation from Lightspeed Ventures. Simultaneously, the company also announced a previously closed Series A round for $8M; in total, the company has raised just over $40M since being founded in 2019. 

Why This Transaction?

The York IE team chose this as our transaction of the week to show the need for real-time data streaming and talk about the benefits of using an intuitive query language like SQL. Given the growing number of internet-connected devices and continued digitization of businesses, there is no doubt that larger and larger amounts of data will continue to be created. For this reason, businesses should be searching for ways to get more out of their streamed data with less complexity and lower costs. For Materialize, the allure of building a platform using SQL was rooted in the idea that it makes real-time data analysis easier and more efficient. Another glaring advantage of SQL is its pervasive nature within the developer community; using a widely understood query language, like SQL, makes user adoption a much easier endeavor. As stated above, real-time data streaming is a growing trend that has quickly taken precedence over legacy batch processing. Companies cannot rely solely on batch processing anymore given the complexity, frequency and sheer amount of data being processed every second. Data streaming however, offers simultaneous storage and processing and gives users more ability to articulate data. Simply put, data streaming enables companies to be proactive rather than reactive to their data and allows for informed decision making. As more industries are making the push towards automation and digitization, in a post-pandemic world, nearly every company has become a data-driven organization. In recent years, financial institutions have embraced digitization; with the help of data streaming, they are able to parse data to identify fraudulent activity and detect risk associated with default. Other industries like energy and manufacturing are implementing data streaming to help assist them with predictive modeling and system optimization. Regardless of the industry, it is clear that real-time data streaming is the current step in the evolution of data and analytics; organizations will likely continue to rely heavily on their data and real-time analytics to make informed decisions.

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