Cisco Investments
Cisco Investments serves as the corporate investment arm of Cisco Systems, focusing on direct and fund of funds investments primarily within the technology sector. Founded in 1993 and based in San Jose, California, with an additional office in Moscow, the firm targets a diverse range of areas including big data and analytics, the Internet of Things (IoT), cloud technologies, cybersecurity, and data center solutions. Cisco Investments actively participates in venture capital, investing in start-ups, early-stage, later-stage, and pre-IPO companies, particularly in key markets such as China, India, Israel, and various regions in Europe. In India, the firm emphasizes early-stage and growth-stage investments in next-generation technologies, including smart city initiatives and financial services. The firm typically invests between $0.5 million and $15 million, aiming for ownership stakes of 5 percent to 20 percent in its portfolio companies. Cisco Investments has a robust portfolio, with over 80 direct investments and substantial Limited Partner positions in various funds globally.
Dremio Corporation, founded in 2015 and based in Santa Clara, California, develops a structured query language query engine software that enhances data accessibility and analytical processing. The company's flagship product, a data lake engine, allows users to perform queries directly against data lake storage, significantly improving query speed and enabling a self-service semantic layer. Dremio empowers business users to curate data from various sources, facilitating greater self-sufficiency among data consumers, including data engineers, analysts, and scientists. By reimagining data lake services, Dremio eliminates the need for traditional data movement to proprietary warehouses, thus streamlining analytics and maximizing the value derived from data.
Dremio Corporation, founded in 2015 and based in Santa Clara, California, develops a structured query language query engine software that enhances data accessibility and analytical processing. The company's flagship product, a data lake engine, allows users to perform queries directly against data lake storage, significantly improving query speed and enabling a self-service semantic layer. Dremio empowers business users to curate data from various sources, facilitating greater self-sufficiency among data consumers, including data engineers, analysts, and scientists. By reimagining data lake services, Dremio eliminates the need for traditional data movement to proprietary warehouses, thus streamlining analytics and maximizing the value derived from data.
Dremio Corporation, founded in 2015 and based in Santa Clara, California, develops a structured query language query engine software that enhances data accessibility and analytical processing. The company's flagship product, a data lake engine, allows users to perform queries directly against data lake storage, significantly improving query speed and enabling a self-service semantic layer. Dremio empowers business users to curate data from various sources, facilitating greater self-sufficiency among data consumers, including data engineers, analysts, and scientists. By reimagining data lake services, Dremio eliminates the need for traditional data movement to proprietary warehouses, thus streamlining analytics and maximizing the value derived from data.
Dremio Corporation, founded in 2015 and based in Santa Clara, California, develops a structured query language query engine software that enhances data accessibility and analytical processing. The company's flagship product, a data lake engine, allows users to perform queries directly against data lake storage, significantly improving query speed and enabling a self-service semantic layer. Dremio empowers business users to curate data from various sources, facilitating greater self-sufficiency among data consumers, including data engineers, analysts, and scientists. By reimagining data lake services, Dremio eliminates the need for traditional data movement to proprietary warehouses, thus streamlining analytics and maximizing the value derived from data.
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