We provide the Best Performance Appraisal Software, BI, Talend ETL, Looker, LookML, Data Analytics, Kafka Kibana, Grafana, Hadoop, Big Data Business Intelligence Predictive Analytics solutions and Many more Best services. Has a decade of experience in Big Data Business Intelligence Predictive Analytics. We architect, develop and implementing 250+ end-to-end BI. Big Data Business Intelligence Predictive Analytics both for enterprises and ISVs

BIG DATA – HADOOP
Struggling with unstructured data? Want to enjoy higher profits with fewer efforts to analyze the data? Embark on to cost-effective solution and emerging technology - Big Data. Big Data Hadoop curtails the human efforts in analyzing the vast data. It expedites timely insights to make decisions and provides exceptional solutions for hard-to-solve problems.
DEFTeam organizes the ample data using Big Data Hadoop by providing solutions based on integrating Hive and HBase, helping customers to have scalable and optimized solutions. We utilize open source, Enterprise & in-memory BI and analytical tools to build comprehensive and pertinent solutions and support that you require. Leverage the power of Big Data Hadoop and scale your data framework with the leading data integration and data quality platforms built for cloud and on-premises.

What is Hadoop?
Apache Hadoop, an open-source reliable and scalable software comes with a Java-based framework, that facilitates to store large data sets on clusters of commodity hardware. Hadoop is platform compatible and works on the Map-Reduce paradigm. It is designed to process the data in parallel on various nodes from a single server, thus allowing the users to write and test distributed systems. This can even detect and handle the faults at the application layer itself for uninterrupted operation.
Hadoop empowers following assets:
• Scalable – Hadoop is scalable as it can store large data sets across huge servers that operate in parallel, enabling the application to run on thousands of nodes simultaneously
• Cost effective - Hadoop is economic, as this can scale and process massive data, that decreases the cost per terabyte of storage, which in turn makes it affordable to manage all your data.
• Flexible – Hadoop can be utilized for a broad range of purposes viz. data warehousing, fraud detection, log processing, etc. and it can even derive the valuable insights from the social media and email conversations.
• Fault tolerant – As servers can be dynamically added or removed, Hadoop can easily detect the faulty nodes on the top layer of the networking model itself due to its uninterrupted operation. As replicated data is sent to other nodes, Hadoop utilizes that replicated data in case of any node unavailability.

Hadoop HIVE:
Hive is an open-source ETL and data warehousing tool utilized for data encapsulation, ad-hoc queries and analyzing the huge datasets stored in Hadoop compatible file systems. As Hive works similar to traditional database systems, Hadoop enables SQL developers to query the data using HQL (Hive Query Language). Hive has peculiar functionality compared to relational databases. Hive works efficiently as it can process queries and get results in no time. Hive uses data storages based on the size of users. Hive supports partition and buckets mechanism for easy retrieval of data. Hive also enables data serialization to increase flexibility in schema design.
Hadoop Database / HBASE:
HBase (Hadoop database) is an open-source Java based distributed, versioned, column-oriented database model and provides a big table like capabilities to Hadoop. HBase is used when we need random, real-time read/write access to your Big Data and runs on top of Hadoop cluster. Unlike traditional rigid schemas, HBase is ideal for storing unstructured and semi-structured data.