Big Data

Unleash smarter insights to achieve stronger outcomes

Big Data, coupled with AI & Analytics, can offer organizations unlimited intelligent opportunities for improving day to day business operations. As companies look for their competitive advantage over competitors, it becomes extremely important to know your data and how to use it. AI or any other intelligent tool is only as smart as the insights that fuel it. We can help you unlock powerful analytics insights by tapping into data you didn't even know you had.

As technology advancements happen at a rapid pace, using the right tool becomes extremely important for gaining technological benefits. Some tools that can help Organizations to achieve greater and stronger results are:

• Hadoop: Apache Hadoop is an open source framework that is used to efficiently store and process large datasets ranging in size from gigabytes to petabytes of data. Instead of using one large computer to store and process the data, Hadoop allows clustering multiple computers to analyze massive datasets in parallel more quickly.

• Scala: Apache Scala, a Robust and High-Caliber programming language that redefined our understanding of big data. Scala, a compiler based and a multi-paradigm programming language which is compact, fast and efficient, is capable enough to outrun the speed of the fastest existing programming languages.

• Spark: Apache Spark, an open source, distributed processing system commonly used for big data workloads. Apache Spark uses in-memory caching and optimized execution for fast performance, and it supports general batch processing, streaming analytics, machine learning, graph databases, and ad-hoc queries.

• NoSQL Databases: NoSQL databases are purpose built for specific data models and have flexible schemas for building modern applications. NoSQL databases are widely recognized for their ease of development, functionality, and performance at scale. For example, the Apache Cassandra database is designed for scalability and high availability without compromising performance. The Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data.

• ETL tools: Extract, Transform and Load (ETL) is the process used to turn raw data into information that can be used for actionable business intelligence (BI). An ETL tool, such as Talend, is an instrument that automates this process by providing three essential functions:

  • Extraction of data from underlying data sources

  • Data transformation in order to meet the data model of enterprise repositories like data warehouses

  • Data loading into target destination

• Distributed Messaging System: Event streaming is the practice of capturing data in real-time from event sources like databases, sensors, mobile devices, cloud services, and software applications in the form of streams of events. Applications are built to store these event streams durably for later retrieval to manipulate, process, and react to the event streams in real-time as well as retrospectively. These systems also route the events to other destination systems as needed. Event streaming thus ensures a continuous flow and interpretation of data so that the right information is at the right place, at the right time.

  Kafka, an event streaming tool, is a distributed system consisting of servers and clients that communicate via a high-performance TCP network protocol. Kafka combines three key capabilities so you can implement your use cases for event streaming end-to-end with a single solution:

  • To publish (write) and subscribe to (read) streams of events, including continuous import/export of data from other systems.

  • To store streams of events durably and reliably for as long as the business demands.

  • To process streams of events as they occur real-time or retrospective.