ExcelR Kolkata

  Big data has become the cornerstone of modern analytics, and with the exponential growth of data, efficient data processing tools are more important than ever. Apache Hadoop has long been a preferred framework for handling large datasets across distributed environments. However, for users who aren’t seasoned Java programmers, writing complex MapReduce jobs can be daunting. This is where Pig Latin steps in — a high-level scripting language that simplifies data transformation tasks in Hadoop. In this blog, we'll explore what Pig Latin is, how it fits into the Hadoop ecosystem, and how you can use it to write data transformation scripts like a pro. Whether you're a data engineer, analyst, or pursuing a Data Scientist Course in Pune , understanding Pig Latin will give you a strong edge in handling big data efficiently. What is Pig Latin? Pig Latin is the scripting language used with Apache Pig , a platform developed by Yahoo to process large data sets. Pig runs on Hadoop and tra...

  Mumbai, often referred to as the financial capital of India, is also emerging as a major hub for technology and data science. As industries across the globe are embracing data-driven decision-making, the role of a data scientist has become increasingly vital. If you’re considering pursuing a data scientist course in Mumbai , or are already working in this field, you’ll find that the city offers ample opportunities, attractive salaries, and a vibrant lifestyle. The Growing Demand for Data Scientists in Mumbai Mumbai has long been a center for various industries such as finance, entertainment, retail, and more. With the rise of data-driven technologies, data science is now playing a pivotal role in business strategies, making data scientist course a promising career . Companies in these sectors are investing heavily in data analytics, AI, and machine learning, creating a significant demand for skilled data scientists. The city has a wide range of opportunities for professionals, f...

  In today’s data-driven world, handling massive volumes of data efficiently is crucial for businesses and organisations. Big data technologies like Hadoop have revolutionised how data is stored, processed, and analysed. But as the volume and complexity of data grow, managing the sequence and coordination of multiple jobs becomes challenging. That’s where Oozie workflows come into play. Apache Oozie is a powerful workflow scheduler that automates the execution of complex data processing pipelines within the Hadoop ecosystem. In this blog, we will explore how Oozie helps streamline big data workflows and why it’s an essential tool for data scientists, data engineers, and data analysts. What is Apache Oozie? Apache Oozie is a Java-based workflow scheduler system designed specifically for managing Hadoop jobs. It allows data scientists to define a sequence of actions—such as MapReduce, Hive, Pig, or Shell scripts—and manage their execution in a defined order. Each workflow is describ...

  Achieving high efficiency is crucial for smooth and cost-effective operations in big data processing. One effective method to enhance the performance of MapReduce jobs is through data locality. This minimises the need for data transfer across the network, leading to faster processing and reduced costs. Mastering MapReduce optimisation through data locality is necessary for professionals looking to refine their big data skills. Understanding Data Locality in MapReduce Data locality refers to the practice of processing data as close as possible to its storage location. In distributed computing frameworks like Hadoop, moving large volumes of data between nodes can be time-consuming and expensive. By keeping computation close to the data, processing time is significantly reduced, and network congestion minimises. Importance of Data Locality in MapReduce MapReduce is a fundamental programming model for processing large datasets across a distributed cluster. The efficiency of a MapRedu...