A big data storage facility has many commodity servers connected to a high-capacity disk to help analytic applications written to crunch massive volumes of data. The framework relies on Massively Parallel Computing databases to interpret data from several sources. In this article, we will be discussing more how BIg Data is stored and managed in an organization.
Hadoop is an open-source platform written in the Java programming language. HDFS extends data processing through hundreds or even thousands of server nodes without an output hit. In this way, through its MapReduce part, Hadoop distributes processing as a safeguard against catastrophic failure. Multiple nodes act as a data analysis center at the edge of a network.
When a query arrives, MapReduce performs the processing directly on the storage node where the data resides. After the study is complete, MapReduce collects the aggregate findings from each server and “reduces” them to produce a single consistent response.
Big Data Management Best Practices
But how can companies overcome the complexities of big data management and reap the benefits of their efforts? Experts propose a range of best practices:
Involve staff members from all related divisions in the attempt to handle big data. Big data management means writing strategies, policy-making, and changing corporate culture—not only investing in technologies. To be successful in these efforts, it helps to include as many people as possible in the process. It has IT staff members as well as company participants and, of course, executive sponsors.
Establish a written data lifecycle management plan and policies. Getting a formal strategy makes it much more likely that it can enforce the approach through the organization. Also, many companies prefer to have their data lifecycle management activities written for regulatory purposes.
Identify and secure classified material. With cyber threats and press leaks appearing every day, companies are more conscious than ever of the need to secure company and consumer information. Data protection teams need to ensure that the confidential data in their databases are sufficiently protected. Data monitoring teams are up to date with the new defensive tactics and techniques.
Deploy strict identification and access security controls, including audit trails. A crucial aspect of any data protection strategy is to ensure that only approved employees can access or communicate with confidential data and monitor who has accessed or used the data and when. Again, these controls can also be necessary for regulatory purposes.
Enable data sharing through the company. According to the MIT report, “Companies that exchange data internally get more benefit from their research. And businesses that are the most advanced in analytics are most likely to exchange data outside their business borders.”
Consider appointing a Chief Information Officer (CDO). This executive position is becoming more and more common in large companies. The New Vantage survey showed that 55.9 percent of the executives surveyed said their company had a CDO. When questioned what the CDO should do, 48.3 said it should drive creativity and data culture, while 41.4 percent said it should treat data as an enterprise asset. Less than 4% said the position was needless.
If you want to ace the best practices of Big Data, then go for a big data course in Malaysia to know more about the technology.
