Online or onsite, instructor-led live Apache Druid training courses demonstrate through interactive hands-on practice how to perform data analysis using Druid.
Druid training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Yokohama onsite live Apache Druid trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
The centre is located within a 5-minute walk from JR Kannai station and a 3-minute walk from Yokohama Blue Line Subway’s Ka...
The centre is located within a 5-minute walk from JR Kannai station and a 3-minute walk from Yokohama Blue Line Subway’s Kannai station. On the north side of the centre is the traditional business district lined with governmental offices, including the prefectural office, Yokohama’s city hall, customs , and port authorities. The area is home to a large number of import / export companies. The city is known for its international air which attracts expats as well as the good old cultural heritage loved by tourists. Tourism thrives here, with many attractions, hotels near the waterfront and the retro downtown area of Motomachi. Yokohama station, one of the biggest hubs in the Tokyo metropolitan area is less than a 10 minute train-ride from this centre. Yokohama station connects to many railway companies and you will reach Tokyo or Shibuya station in 30 minutes.
Apache Druid is an open-source, column-oriented, distributed data store written in Java. It was designed to quickly ingest massive quantities of event data and execute low-latency OLAP queries on that data. Druid is commonly used in business intelligence applications to analyze high volumes of real-time and historical data. It is also well suited for powering fast, interactive, analytic dashboards for end-users. Druid is used by companies such as Alibaba, Airbnb, Cisco, eBay, Netflix, Paypal, and Yahoo.
In this instructor-led, live course we explore some of the limitations of data warehouse solutions and discuss how Druid can compliment those technologies to form a flexible and scalable streaming analytics stack. We walk through many examples, offering participants the chance to implement and test Druid-based solutions in a lab environment.
Format of the Course
Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
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