Cloudera Hadoop Administration Course

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What is Cloudera?

Cloudera, Inc. is an American software business that specializes in enterprise data management systems that make extensive use of Apache Hadoop. The firm had roughly 1,800 clients as of January 31, 2021. Cloudera offers the Cloudera Data Platform, a suite of cloud services and data processing solutions. Some of these services are delivered via public cloud servers like Microsoft Azure or Amazon Web Services, while others are delivered via private cloud services that need a subscription. Cloudera sells these tools for machine learning and data analysis applications.

What are the Advantages of using Cloudera?

There are several reasons why your choice of data platform is important. It will serve as the cornerstone for your digital transformation, allowing you to get actionable information and deliver enormous and demonstrable value to the organization.

The advantages of a unified platform A major source of annoyance is that single-purpose, specialist databases, and technologies are functionally constrained, offering just one method of analytics. This necessitates considerable effort in attempting to integrate disparate products to handle diverse functions such as SQL-driven data warehousing and business intelligence (BI), real-time analytics for IoT, data science machine learning (ML), and/or data engineering and preparation that precedes each of the foregoing. This requirement for integration raises the workload of your staff and considerably delays projects. Furthermore, each new vendor offering that must be incorporated raises product and operations expenses. Not to mention that the possibility of mistakes or security vulnerabilities is exacerbated by the presence of numerous unique security frameworks, each with its own set of capabilities and flaws.

Machine Learning

Machine learning is a significant priority for Cloudera Enterprise. Our data platform enables you to model your business and make predictions that traditional methods cannot. It provides your data scientists with fresh data sources to mix in order to discover new trends without adding risk or responsibility. They can also work directly with ALL data, rather than just a sample downloaded to a laptop, thanks to the platform. Last but not least, the entire data pipeline may be designed and maintained on a single platform, rather than moving data across silos.


Another priority is to upgrade data warehouses with a more current solution. Traditional enterprise data warehouses are inflexible, expensive, and restricted in scale by cost and architecture, as well as in scope to well-defined structured data. They do, however, have a role, and Cloudera Enterprise supplements them, particularly for exploration and self-service analytics. Cloudera Enterprise can also work with less structured data and incorporate technologies such as integrated search and data science, in addition to SQL.


A third element is a realization of how cloud computing has the potential to transform the game. Unfortunately, many cloud analytics platforms aren't as adaptable as you might expect. Try shrinking or expanding AWS Redshift to petabytes, for example, and you'll discover the constraints. Cloudera Enterprise addresses these restrictions with enterprise-grade offerings that use cloud infrastructure while also delivering on promises. The platform also enables you to execute the same solution across hybrid and multi-cloud settings, improving operational efficiency and avoiding cloud vendor lock-in. One step closer to simplification is to automate most of the management, as we have done with Cloudera Altus.

Data Science

Cloudera's single platform for data and machine learning removes silos and accelerates time to value – whether on-premises or in the cloud. Having safe, self-service access to company data increases data scientists' productivity while reducing risk. Access to elastic on-demand resource provisioning provides data scientists with the computational capacity they require for the most demanding analyses. The flexibility, creativity, and value of open-source machine learning tools and libraries are brought to the data through a free choice of Python, R, and Scala support. Not to mention that containerized environments make collaboration, sharing, reproducibility, dependence, and deployment management easier. Overall, the platform aids in the acceleration of data science from research to production.

Data Warehouse

Cloudera Data Warehouse provides high-performance SQL for ad hoc exploration and self-service reporting. It allows for more iterations with more data and uses cases than a standard data warehouse. Users can also use open standard technologies, such as integrated text search, to go beyond SQL for shared data. Cloudera Navigator Optimizer, which can examine specific operations for ease of migration, aids in data warehouse optimization of your current databases. Again, unlike a typical hardware-based data warehouse appliance, Cloudera Enterprise allows you to expand both on-premises and in the cloud while being cost-effective.

Operational Database

Cloudera Enterprise can enable real-time data serving at scale, injecting the most up-to-date information into data-dependent processes and choices. Fast analytics on fast data via a streamlined architecture enables the examination of patterns that encompass even the most current data. To satisfy the objectives of every use case, analytics application developers may employ any data source and any data type, together with the appropriate data storage - NoSQL, relational, or HDFS. The ability to proactively monitor, anticipate and improve IoT, cybersecurity and digital network environments by promptly recognizing and comprehending irregularities is one of the use cases. For developers, linear performance scalability with processing flexibility is a significant benefit. All of these skills contribute to the extraction of real-time insights from large data.

What is Hadoop?

Hadoop is a set of open-source software tools that make it easier to tackle problems requiring large volumes of data and processing by using a network of many machines. It's a software framework based on the MapReduce programming concept for distributed data storage and processing. Hadoop was designed with the goal of being used on commodity hardware computer clusters, which is still the case today. Since then, it's been employed on more powerful hardware clusters. Hadoop's modules are based on the assumption that hardware faults would occur often and that the framework should manage them automatically. Hadoop is an open-source platform for dealing with huge datasets that are used by developers and others (Big Data). Hadoop also deals with applications by executing them on open-source clusters of such hardware. Hadoop provides us with the safest method of storing data in a series of phases that are regulated by its components.

What is Cloudera Hadoop Administration?

A Cloudera Certified Administrator for Apache Hadoop (CCAH) certification validates your technical knowledge, abilities, and competence to configure, install, manage, and secure an Apache Hadoop cluster.

How much Hadoop Administrator earns?

In India, the average income for a Cloudera and Hadoop Administrator is 10.4 Lakhs per year (INR 86.7k per month). Salary estimations are based on 9 salaries submitted by Cloudera and Hadoop Administrators from various industries.

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Course Syllabus

Getting Started 11 lectures 17 mins
Introduction Preview 01:42
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