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You're reading from Learning Hunk

Product typeBook

Published inDec 2015

Reading LevelIntermediate

Publisher

ISBN-139781782174820

Edition1st Edition

Languages

Java

Tools

Hadoop

Concepts

Data Analysis

Authors (2):

Dmitry Anoshin

Sergey Sheypak

View More author details

Knowledge objects

Hunk has the same capabilities as Splunk; as a result we can create various knowledge objects that can help us explore big data and make it more user-friendly.

Tip

A knowledge object is a configuration within Hunk that uses permissions and is controlled via the Hunk access control layer. Knowledge objects can be scoped to specific applications. Read/write permissions for them are granted to roles.

To work with knowledge objects, go to the KNOWLEDGE menu under Settings:

There are various knowledge objects available in Hunk. We encountered SPL, reports, dashboards, and alerts in the previous chapter. Let's expand our knowledge of Hunk and explore additional knowledge objects.

Tip

For more information about knowledge objects, see: http://docs.splunk.com/Documentation/Splunk/latest/Knowledge/WhatisSplunkknowledge.

Field aliases

Field aliases help us to normalize data over several sources. We can create multiple aliases in one field.

Tip

Aliases should be applied after field extraction...

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Learning Hunk

Published in: Dec 2015Publisher: ISBN-13: 9781782174820

Authors (2)

Dmitry Anoshin

Dmitry Anoshin is a data-centric technologist and a recognized expert in building and implementing big data and analytics solutions. He has a successful track record when it comes to implementing business and digital intelligence projects in numerous industries, including retail, finance, marketing, and e-commerce. Dmitry possesses in-depth knowledge of digital/business intelligence, ETL, data warehousing, and big data technologies. He has extensive experience in the data integration process and is proficient in using various data warehousing methodologies. Dmitry has constantly exceeded project expectations when he has worked in the financial, machine tool, and retail industries. He has completed a number of multinational full BI/DI solution life cycle implementation projects. With expertise in data modeling, Dmitry also has a background and business experience in multiple relation databases, OLAP systems, and NoSQL databases. He is also an active speaker at data conferences and helps people to adopt cloud analytics.
Read more about Dmitry Anoshin

Sergey Sheypak

Sergey Sheypak started his so-called big data practice in 2010 as a Teradata PS consultant. His was leading the Teradata Master Data Management deployment in Sberbank, Russia (which has 110 billion customers). Later Sergey switched to AsterData and Hadoop practices. Sergey joined the Research and Development team at MegaFon (one of the top three telecom companies in Russia with 70 billion customers) in 2012. While leading the Hadoop team at MegaFon, Sergey built ETL processes from existing Oracle DWH to HDFS. Automated end-to-end tests and acceptance tests were introduced as a mandatory part of the Hadoop development process. Scoring geospatial analysis systems based on specific telecom data were developed and launched. Now, Sergey works as independent consultant in Sweden.
Read more about Sergey Sheypak

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