{"product_id":"big-data-concept-tools-techniques","title":"Big Data – Concept, Tools \u0026 Techniques","description":"\u003cdiv class=\"dt-product-description-v7\"\u003e\n\u003ch2 class=\"dt-heading-xl\"\u003eBig Data Training: Concepts, Tools and Techniques\u003c\/h2\u003e\n\u003cdiv class=\"dt-body-premium\"\u003e\n\u003cp\u003eBig Data – Concept, Tools and Techniques is a 36-course Learning KIT that teaches you how to work with large-scale data environments using industry-standard tools including \u003cstrong\u003eHadoop, Apache Spark, and NoSQL databases. \u003c\/strong\u003eThe training covers the full spectrum from Big Data fundamentals through to real-time stream processing and applied data analytics. It is built for aspiring data engineers, analytics professionals, and IT practitioners who want to develop practical Big Data skills. Expert tutor support is available 24\/7 through the DiviTrain platform.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-grid-v7\"\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eWhat this training includes\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003e32+ hours of e-learning — 365 days access\u003c\/li\u003e\n\u003cli style=\"font-weight: bold;\"\u003e\u003cstrong\u003e5 hours of hands-on labs included\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli\u003eExpert tutor support available 24\/7\u003c\/li\u003e\n\u003cli\u003eOrganizations seeking team-wide training can explore our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003ecorporate volume solutions\u003c\/a\u003e.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"dt-container-v7\"\u003e\n\u003ch3 class=\"dt-heading-card\"\u003eReady for roles like\u003c\/h3\u003e\n\u003cul class=\"dt-list-premium\"\u003e\n\u003cli\u003eBig Data Engineer\u003c\/li\u003e\n\u003cli\u003eData Engineer\u003c\/li\u003e\n\u003cli\u003eData Architect\u003c\/li\u003e\n\u003cli\u003eAnalytics Engineer\u003c\/li\u003e\n\u003cli\u003eData Warehouse Engineer\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eWhat this Big Data training covers\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBig Data Fundamentals and the 5 V's \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eUnderstand what defines Big Data and why traditional data tools fall short at scale. You will explore the five core dimensions — Volume, Velocity, Variety, Veracity, and Value — and learn how distributed computing addresses each one in real production environments.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHadoop Architecture and HDFS \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLearn how the Hadoop Distributed File System stores and manages large datasets across clusters. Topics include NameNode and DataNode architecture, data replication strategies, and the core principles of cluster setup and administration.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eMapReduce Programming Model \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eWork with the MapReduce paradigm for distributed batch processing. You will learn how Mapper and Reducer functions divide and process data across nodes, and how Hadoop manages job execution and fault tolerance at scale.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eHadoop Ecosystem: Hive, Pig, Sqoop, Flume, and Oozie \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eExplore the broader Hadoop toolset used in production data environments. This module covers Hive for SQL-style querying, Pig for data transformation scripting, Sqoop for relational database integration, Flume for log ingestion, and Oozie for workflow scheduling.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eApache Spark Core and RDDs \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eGet hands-on with Apache Spark's core engine and the Resilient Distributed Dataset model. You will learn how Spark's in-memory processing delivers significant performance improvements over MapReduce for iterative and interactive workloads.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSpark SQL and DataFrames \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eUse Spark SQL and the DataFrame API to query and transform large structured datasets. This module covers running SQL operations on distributed data, optimizing queries, and integrating Spark SQL with existing data warehouse workflows.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eSpark Streaming and Real-Time Processing \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBuild real-time data pipelines using Spark Streaming and micro-batch processing. You will work with continuous data sources, apply transformations on live streams, and understand the architecture behind low-latency analytics systems.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eNoSQL Databases: MongoDB, Cassandra, and HBase \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eLearn when and how to use non-relational databases in Big Data architectures. This module covers document storage with MongoDB, wide-column storage with Apache Cassandra, and Hadoop-native storage with HBase — including CRUD operations, indexing, and replication patterns.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eData Ingestion, ETL, and Pre-Processing \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eUnderstand how raw data flows from source systems into Big Data platforms. Topics include ETL pipeline design, data quality and cleansing, schema-on-read versus schema-on-write, and the distinctions between data lake and data warehouse architectures.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eBig Data Analytics and Applied Use Cases \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eApply Big Data tools to real analytical problems across industries including retail, finance, healthcare, and telecommunications. You will explore how organizations use Spark MLlib and batch analytics to extract insight from large datasets and support data-driven decisions.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eWhere can Big Data skills take your career\u003c\/h3\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCareer paths and next steps after this Big Data training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBig Data skills are in high demand across cloud-native companies, financial institutions, and technology teams building data-driven products at scale. After completing this training, many professionals move into \u003ca href=\"https:\/\/www.divitrain.com\/products\/mlops-machine-learning-operations\"\u003eMLOps\u003c\/a\u003e to learn how to deploy and maintain machine learning models in production, or progress toward cloud data engineering roles on platforms like Microsoft Azure.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003ch3 class=\"dt-heading-section\"\u003eFrequently Asked Questions\u003c\/h3\u003e\n\u003cdiv class=\"dt-faq-accordion-v7\"\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat Big Data tools and frameworks does this training cover \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe training covers the core tools used in modern Big Data environments, including Hadoop and its ecosystem (HDFS, Hive, Pig, Sqoop, Flume, Oozie), Apache Spark (Core, SQL, Streaming), and NoSQL databases including MongoDB, Apache Cassandra, and HBase. You will also work with ETL concepts, data pipeline design, and applied analytics use cases across all 36 courses.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eDo I need programming experience to start this Big Data training \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eBasic familiarity with programming concepts is helpful, particularly for the Spark and NoSQL modules. The training starts from fundamentals and does not assume prior Big Data experience. Modules covering Spark SQL and DataFrame operations will be easier to follow if you have a working knowledge of SQL or Python.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eWhat is the difference between Hadoop and Apache Spark \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eHadoop is a distributed storage and batch processing framework built around HDFS and MapReduce. Apache Spark is a faster in-memory processing engine that can run on top of Hadoop or independently. Spark processes data significantly faster than MapReduce for iterative workloads, which is why it has become the standard engine for Big Data analytics, machine learning, and streaming. This training covers both frameworks so you understand when to use each.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eIs the exam voucher included and how do I register for the exam \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eThe exam voucher is not included in this training. The exam is administered globally by Pearson VUE, either at an authorized testing center or via online proctoring. Once your preparation is complete, you register and purchase your exam voucher directly through the official certification or Pearson VUE website.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003cdetails class=\"dt-acc-item-v7\"\u003e\n\u003csummary\u003eCan my team or organization get certified together \u003cspan class=\"dt-acc-toggle\"\u003e+\u003c\/span\u003e\u003c\/summary\u003e\n\u003cdiv class=\"dt-acc-content\"\u003eYes. DiviTrain offers volume licensing for teams and organizations looking to upskill at scale. Whether you are certifying a small IT team or rolling out training across departments, our corporate solutions provide flexible access and invoicing options. Visit our \u003ca href=\"https:\/\/www.divitrain.com\/pages\/for-teams\"\u003eFor Teams page\u003c\/a\u003e to learn more.\u003c\/div\u003e\n\u003c\/details\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"DiviTrain.com","offers":[{"title":"Default Title","offer_id":54757018337605,"sku":null,"price":399.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0280\/0350\/0118\/files\/BigData_a206540a-0fa3-4e32-a2b2-da4d947d339a.webp?v=1748028876","url":"https:\/\/www.divitrain.com\/nl-nl\/products\/big-data-concept-tools-techniques","provider":"DiviTrain.com","version":"1.0","type":"link"}