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Harnessing The Power Of Hadoop For Analytical Reporting

The hype and excitement of Big Data makes it easy to believe that Hadoop can solve large numbers of big data problems. Hadoop is a powerful technology and is designed for different data types and workloads. It is a highly cost-effective technology used for staging raw data that can be either structured or non-structured. These data can be refined and therefore prepared for analytics. In fact, there is no denying the fact that the field of analytical reporting has benefited immensely with the advent of Hadoop. It helps in avoiding costly upgrades of existing databases and warehouse appliances when the capacity is consumed quickly. Raw and unused data are consumed quickly, but Hadoop solves the problem.

Dealing With The Tsunami Of Data:

Most companies face big data challenges. Growing volumes of data like enterprise resource planning software and customer call center records have created a tsunami of data. Most companies know the process of collecting, storing and analyzing the operational data. However, these multi-structural data are too variable and dynamic to be captured in a cost-effective manner. Some companies are also looking beyond the big data volumes and focusing on the analytics value. It is said that Hadoop is a big analytical solution that can transform huge volumes of high velocity and complex data into pure business solutions.

Integration With Data Management Infrastructure:

Before using Hadoop in any field, it is important to integrate the technology with the rest of data management infrastructure. Consequently, it helps in bridging Hadoop with other data processing and analytics systems. Before the deployment of Hadoop, most organizations have to get involved in time-consuming hand coding of data processing. This resulted in errors and maintenance issues. However, Hadoop utilizes the existing skillset and induces the need to show skills in programming in different languages like Hive, MapReduce and pig.

Exploring The Best Alternative:

In fact, big companies are exploring the alternative solution of handling the challenges of converting big data volumes. The solutions are available in MapReduce software framework like Hadoop. It can cost-effectively load, store and refine multi-structured data. A data discovery platform can also be used to integrate with Hadoop so that the power of both can be combined for the perfect analytic framework with SQL-based tools. These are familiar to the analysts and the result is a unified solution to help gain companies a valuable insight from the new and existing data.

Addressing Multiple Factors:

The power of Hadoop should be harnessed for analytical reporting in addressing multiple factors. Some of these factors include:

  • Volume- The amount of data generated by companies continues to grow. This needs to be managed properly.
  • Velocity- Data continues to change at an increasing speed making it difficult for companies to capture and analyze. Hadoop can be utilized to decipher real-time analytics.
  • Variety- Collecting only transactional data is not enough. Analysts are interested in new types of data that add richness and supports detailed analyses.

There are various other factors that need to be addressed for immense growth in the near future.