Information Technology may always face challenges in managing data through the internal data stores. There has been a need for improving the methods of analysis, data storage and the final outcome to the end users. If all the data management process can be done in an effective manner, business decisions can be taken wisely. One of the problems nowadays is the huge volume of the data and new strategies are to be applied for data storage. Hadoop can be used as one of the solutions.
How can Hadoop help with the storage of the huge volume of data?
Hadoop is a free programming framework which is based upon Java. Within a proper computing environment, this particular framework can support processing of huge data and storage and makes them ready for distribution. It generally uses the free license for distributing data through intensive applications. The machines are not required in sharing the memory space or disk while the architecture gets distributed.
As data can be placed in various locations, they can become disparate in various servers. Hadoop can help in tracking the exact location. It can also ensure accessibility by providing various copies of data. It can also provide the nodes of single master and the multiple workers through different clusters. The control function is generally allotted to the master nodes, who can schedule the services to the various worker nodes.
Now, let us go through some of the applications which the database experts must know.
- Processing of images
- Log Analysis
- Web crawling process
- Processing of texts
- Achieving with relational or tabular data which ensures the data compliance
- Marketing analytics
- Processing of XML messages
- Click stream analysis
- Data mining
- Machine learning
Challenges Of Managing A Database In Hadoop:
Though Hadoop has been widely accepted by many IT companies, there are still many challenges that are faced by the database experts.
SQL on Hadoop : Huge databases can be stored with the help of Hadoop. Besides using the predetermined data pipelines, the organizations are now expecting increased value from their data by processing the interactive access to the data through proper business analysis. There are various frameworks for Hadoop which can offer interactive SQL. Though it cannot be compared with the conventional OLAP database, the challenge is to select the best among the available ones. Many advantages of strategies can be found but there are various downsides regarding the simplicity of the process. Though the approach is very popular , it has to go through many challenges as the entire process is not that simple compared to the conventional approaches.
Select Vendors: Many vendors are available in the market and you are required to choose them wisely. The original Hadoop framework can only be used be few companies with the deployment within the production environment. Vendors like Oracle may include hardware also and things may actually get complicated when you start negotiation with the vendors. Even the experienced Hadoop users may find difficulty in the configuration of the components and the managers.
Avail Big Data Engineers: The engineers must have enough experience with a strong IT team in the data management process. The company personnel must possess specific skills in the big data and the technological stuff beyond their knowledge in Python, Java, C++. The developers must be capable of delivering which can be evaluated in the future.
The Hadoop beginner should not back out by observing the challenges of Hadoop in the data management. There can be a host of advantages that can be reaped out by deploying Hadoop in the enterprises. Hadoop can display further improvement with the help of the Apache project applications and can reach up to an increased level of acceptance and recognition in the market.