Case Study

Malwarebytes Case Study

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CASE STUDY Predicting, Detecting, and Eliminating Online Threats: Malwarebytes Industry: Technology To predict, detect, and neutralize emerging threats, Malwarebytes processes billions of threat telemetry records daily. The company then performs advanced analytics on this data to identify potential threats and runs ML and AI models to determine what action to take to protect its customers. Malwarebytes formerly relied on a third party on-premises deployment to ingest and process this data. But this system proved inadequate. For example, the pipeline took a few days to complete Extract-Transform- Load (ETL) on one data stream alone. And, queries on the ingested data were painfully slow. That wasn't all. It was also expensive—and was becoming increasingly more so as Malwarebytes' data grew exponentially. At the same time, little was offered in the way of support. "We started getting into issues where we were all on our own," says Malwarebytes' Senior Manager, Data Engineering - Data & AI, Sujay Kulkarni. Malwarebytes needed some way to modernize its big data processing to improve turnaround time while also keeping costs down. And the company needed more than just a vendor to support this operation—it needed a partner. So, in 2016, it turned to Qubole. About Malwarebytes Malwarebytes is a cybersecurity company that produces anti- malware software for a variety of platforms. The company offers consumers free, premium, and enterprise-grade versions of Malwarebytes, which detect, remove, and remediate computer malware. Malwarebytes uses machine learning (ML) and artificial intelligence (AI) to identify and predict emerging threats before they infect machines. Business Problem Overview

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