Hadoop is a software system developed by Apache that allows a company’s data science team to process for analytical purposes large sets of data that are located on distributed servers. The software framework is mainly used by those companies that want the capability of extracting unstructured data to improve things like business performance and customer relationship management. This unstructured data is known in the industry as big data. Every company that conducts physical and electronic transactions has access to big data, but it was not until recently that corporate leaders began to fully recognize big data’s potential to help them to forecast trends needed to improve competitive advantage. Large businesses were at an advantage because they could purchase specialized hardware and hire the human resources that are needed to prepare the diverse data for analysis. Convenient features like Excel reporting in Hadoop allow small businesses to harness the power of big data analytics as even non-technical users are able to access large data sets from inexpensive, off the shelf servers for data analysis projects. Here are some other reasons why Hadoop is considered a leading tool for corporate data science teams.
Use Hadoop With Leading Storage Technology
Hadoop has leveled the playing field for companies that want to effectively use big data to optimize their business processes. For example, many medical companies collecting genetic data for advanced personalized medicine initially lacked the storage capacity needed for effective big data analysis. Today, businesses of varying sizes use cloud storage options to expand their storage capabilities, and one of the most popular brands is Google Cloud Storage. The value of Hadoop is well known in the information technology industry, and Google has responded by building a custom connector that integrates Google Cloud Storage with Hadoop. Additionally, providers of storage area network and virtualization storage options have plans to integrate their products and services with Apache’s Hadoop.
Tighten Up Big Data Security Using Third Party Tools and Add-Ons
Data security remains a hot button issue for many companies, non profit organizations and government agencies. It seems that no organization is immune to attacks by hackers who want to steal information or corrupt the integrity of stored data. As a result, many businesses are forced to pay fines or legal reparations for not adequately protecting the information entrusted to them, and other businesses experience productivity losses. The storage and processing of big data by numerous companies just opens up a new path for cyber criminals because they have greater amounts of unsecured data to exploit. Hadoop was not originally built with security mechanisms in place, but third party tools like IBM InfoSphere Optim Data Masking, Cloudera Sentry and DataStax Enterprise have incorporated authentication and data privacy features into their versions of Hadoop. Many of these tools provide for the authentication of Hadoop processes, services and users; they also allow for the encryption of the Hadoop file system and data access blocking. Maintenance and customer support are additional benefits of purchasing these distributed, third party versions of Hadoop versus using the free, original Apache product.
Improve Big Data Processing Through Hadoop Integration With Popular IT System Brands
A great advantage of using Hadoop over other business intelligence software is the capability that it provides to developers and analysts to quickly extract and process large groupings of data. The efficiency of processing is dependent on many factors including the location of the data and the server platform used. Many businesses trust Microsoft’s brand and have outfitted their organization with the company’s servers, operating system and application software. Although Microsoft’s products have been known not to be compatible with competing software systems, the computing giant has taken great strides to update their flagship MS SQL Server product so that it and its Parallel Data Warehouse utility connects with Hadoop. Microsoft Office applications like Excel have also been updated to integrate with the Apache product; this functionality allows Hadoop users to import data analysis output into a spreadsheet format. The distributed version of Hadoop that is used by IBM’s InfoSphere BigInsights system also allows Hadoop users to view, analyze, graph and update data from multiple sources using a web based spreadsheet; IBM’s plan was to make their version of Hadoop the preferred one for business users. The fact that Hadoop can be implemented on these many platforms, and the many resources available to those learning it for the first time, make it the ideal product to use.
Modify Hadoop To Extend Functionality
Although the development team for the original Apache Hadoop software positively responds to the user community with value added updates, many businesses want to customize the open source software to quickly meet their organization’s’ unique needs. Hadoop is Java based, but developers do not have to be Java programming experts to make modifications to the software framework. Database developers can use SQL similar scripting languages like Hive and Pig that are exclusively associated with Hadoop to add structure to data sets and import value added customizations into Hadoop.