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Business Intelligence: What is Hadoop?

Hadoop: The New Face of Business Intelligence

Big data has changed the way businesses handle their business intelligence initiatives, requiring them to capture, process, and analyze exponentially larger amounts of information. Traditional business intelligence tools like relational databases are no longer sufficient to handle the level of data businesses are experiencing.

If businesses are going to take advantage of the insights offered by big data—instead of drowning in the flood of useless and irrelevant data—they are going to need new tools to help them handle the data crush.

Enter Hadoop. In just a few short years, Hadoop has become one of the most powerful and widely used tools for turning big data into useful insights.

What is Hadoop exactly?

It may have a strange name, but there’s no reason to intimidated or confused about what Hadoop actually is. Hadoop is simply an open-source software platform, produced by the non-profit Apache Software Foundation, for the storage and processing of massive data sets.

Hadoop is designed to spread files and workloads across clusters of hardware. This arrangement allows for the increased computational power needed to handle massive amounts of data, and helps organizations protect their workloads from hardware failure.

The Hadoop framework is made up of a number of different modules, including Hadoop Distributed File System (HDFS). HDFS distributes very large files across hardware clusters to ensure maximum aggregate bandwidth. Hadoop MapReduce is a programming model for processing very large data sets.

Why do I need to learn about Hadoop?

Simply put, Hadoop has already experienced a very high level of adoption from the business world. It promises to be the standard tool for big data management going forward.

Hadoop is already being used by more than half of Fortune 50 companies, including major names like Yahoo! and Facebook. Eric Baldeschwieler, CEO of Hortonworks, has predicted that as much as half of the world’s data will be processed using Hadoop by the year 2017.

If your business works with data at all, you need to know the name Hadoop. It will touch your organization in some way, if it hasn’t done so already.

What are the advantages of Hadoop?

Hadoop gives your developers the power to conduct batch processing on data sets that include structured, unstructured, and semi-structured data. This makes it a perfect fit for the realities of today’s big data environment.

It also allows it to succeed in ways that traditional business intelligence tools can’t. It is also highly scalable, and offers enterprise-level big data analytics at a price that midmarket companies can afford.

What are the disadvantages of Hadoop?

With so much fanfare around Hadoop, identifying its shortcomings might seem difficult, but they certainly exist. Hadoop isn’t the simple answer to all of your data management problems.

It’s important that you understand what it can and can’t do before you pursue a Hadoop-based big data solution for your business.

Hadoop is a tool aimed specifically at developers. As a result it can segregate tech users from the business users who actually need to make use of data insights.

If the insights you gain from Hadoop data processing aren’t getting into the right hands, then your Hadoop deployment is just wasting your time and resources.

As an open-source framework, Hadoop should be looked at as a work in progress. Many industry analysts have suggested that the current iteration of Hadoop is not mature enough to provide real-time Business Intelligence Security: Hadoopanalytics or ensure the security of sensitive data. Businesses can gain a lot of value by using Hadoop, but they also need to learn about these limitations first.

For more on this topic, read our three part series on the components of a business intelligence solution

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