AMVS offers Hadoop consulting services to help clients to store and analyze their data. Apache Hadoop is a framework for distributed storage and processing of data. It is especially suited to working on very large and disparate data sources.
Using Hadoop, you can load data from many different documents, databases, APIs and services into one large data store, the Hadoop Distributed File System (HDFS). Once your data is in HDFS, it becomes available for use as a database, or data warehouse through Cassandra, HBase, and Hive. It also allows for powerful machine learning with Mahout. General computation tasks can be accomplished easily with Pig or Spark.
Hadoop is at the center of this decade’s big data revolution. This Java-based framework is actually a collection of software and subprojects for distributed processing of huge volumes of data. The core approach is MapReduce, a technique used to boil down tens or even hundreds of terabytes of Internet click stream data, log-file data, network traffic streams, or masses of text from social network feeds.
Many people see in Hadoop the potential to usher in a whole new generation of data-processing capabilities, just as Structured Query Language (SQL) ushered in a revolution in data computing more than 30 years ago. Big data & analytics projects that require processing of a large amount of data, or particularly complex processing are good use cases for Hadoop. It makes scaling up to have many instances running processing tasks in parallel easy.
All Hadoop consulting companies help to install and configure the Hadoop environment, and to implement processes specific to their clients. However, it is more important to avoid the pitfalls of poorly thought out or poorly implemented solutions. The nature of projects with large sets of data that are not well formed means that it’s easy to find correlations that are coincidental or nonexistent. Effective Hadoop consulting requires that consultants really get a great understanding of the client’s business as well as clear communication to ensure that data is presented in an accurate, actionable way.