Big data and analytics training at Bodhih teaches teams how to store, process and analyse large data sets using the Hadoop ecosystem and the tools that have grown from it, including Apache Spark, Hive and cloud data lakes. It is customised for corporate data teams and delivered with hands-on labs, in person or live virtual.
- Standard duration: 5-days, customisable to your needs
- Delivered in person at your location or as live virtual sessions
- Designed with the ADDIE model and evaluated for behaviour change
- Offered by Bodhih since 2008 to 2,000+ organisations across 7 regions
Where and how: big data and analytics training as an in-person workshop in Bengaluru, Mumbai, Delhi NCR, Gurugram, Hyderabad, Chennai, Pune, Kolkata, Ahmedabad and Jaipur; as a live online course; or delivered overseas in Dubai, Singapore and across the Middle East, Asia and Africa.
Big Data Hadoop
Program Overview:
This training will primarily Big data and Hadoop concepts, learning how to deploy Hadoop clusters.
Introduction to Hadoop and HDFS, concepts on Map reduce Programming model, Data Manipulation using pig and hive with hands on practical session.
Training Duration:
5-days Instructor Led Training
Target Audience:
- Anyone who wants to develop big data applications using Hadoop.
- Teams getting started or working on Hadoop based projects.
Training Prerequisite:
Basic programming knowledge is recommended.
Training Outcome:
- Practical Approach
- Hands on training session
- Real time project and case studies
- 24/7 support
Solutions & Services
What participants will be able to do
Understand distributed data processing
Participants explain how HDFS, YARN and MapReduce split storage and computation across a cluster.
Query large data sets with SQL
Analysts and engineers use Hive and Spark SQL to explore and summarise big data.
Build Spark pipelines
Engineers write batch transformations with Spark DataFrames in Python or Scala.
Choose the right storage format
Teams compare row and columnar formats such as Parquet and understand partitioning.
Relate Hadoop to modern platforms
Participants see how on-premises Hadoop concepts map to cloud data lakes and lakehouses.
Deliver an end-to-end analytics flow
Teams ingest, clean, transform and analyse a realistic data set in a capstone lab.
Who should attend
- Developers building or maintaining big data applications
- Data engineers working on Hadoop, Spark or cloud data platforms
- Data analysts who need to query very large data sets
- Teams migrating from on-premises Hadoop to cloud data platforms
- Architects evaluating data lake and lakehouse designs
Recommended program outline
Recommended design, customised to your context after a short needs analysis.
01Big data foundations and Hadoop architectureModule 1 · Day 1+
- What makes data 'big': volume, velocity and variety
- HDFS storage, replication and YARN resource management
- Setting up and exploring a Hadoop cluster
- Hadoop ecosystem tools and where each fits
02MapReduce and data processing conceptsModule 2 · Day 2 (morning)+
- The MapReduce programming model explained
- Writing and running a simple MapReduce job
- Why newer engines such as Spark are now more common
- Combiners, partitioners and job tuning basics
03Data manipulation with Hive and PigModule 3 · Day 2 (afternoon) and Day 3+
- Hive tables, partitions and HiveQL queries
- Pig Latin for data flows on legacy clusters
- File formats: CSV, Avro, ORC and Parquet
04Apache SparkModule 4 · Day 3 and Day 4+
- Spark architecture, DataFrames and lazy evaluation
- Spark SQL and PySpark transformations
- Performance basics: partitioning, caching and joins
- Introduction to structured streaming
05Cloud data platforms and capstoneModule 5 · Day 5+
- Data lakes, lakehouses and open table formats in overview
- Managed big data services on major cloud providers
- Capstone: ingest, transform and analyse a data set end to end
- Data quality, governance and cost considerations
When to choose this
Frequently asked questions
Is Hadoop still worth learning?
Many organisations still run Hadoop clusters, and its core ideas of distributed storage and parallel processing underpin modern data platforms. New projects more often use Spark and cloud data lakes. Bodhih's program covers Hadoop foundations and then moves to Spark and cloud concepts, so teams can support existing systems and plan for what comes next.
What is the difference between Hadoop and Spark?
Hadoop is an ecosystem that includes HDFS for storage, YARN for resource management and MapReduce for processing. Spark is a processing engine that can run on Hadoop or elsewhere. It keeps data in memory where possible, which usually makes it much faster than MapReduce for analytics and iterative work. Many teams use Spark with HDFS or cloud storage.
What skills do I need before big data training?
Basic programming knowledge is recommended, ideally in Python, Java or Scala, along with working SQL and familiarity with the Linux command line. Participants do not need prior Hadoop experience. Bodhih shares a short readiness checklist and can add a Python or SQL refresher for groups that need one.
What is a data lakehouse?
A data lakehouse combines low-cost data lake storage with features traditionally found in data warehouses, such as reliable transactions, schema management and fast SQL queries. It is typically built on open file and table formats in cloud storage. The program explains the concept so teams understand how it relates to their Hadoop experience.
How long is the big data and analytics program?
Bodhih's recommended program is five days of instructor-led training with daily labs and a capstone. Teams focused only on Spark or only on analytics querying can take a shorter, targeted version. The outline, tools and cloud platform used in labs are customised to your environment after a needs analysis.
Who is the Big Data and Analytics in Today's Business World program for?
Anyone who wants to develop big data applications using Hadoop., Teams getting started or working on Hadoop based projects.. Bodhih tailors the examples, case studies and depth to your industry, culture and team level.
Can Big Data and Analytics in Today's Business World be delivered online?
Yes. Big Data and Analytics in Today's Business World can run in person at your location, as live virtual sessions for distributed or hybrid teams, or as a blended journey that adds self-paced learning on Bodhih.org between sessions.
How is the impact of Big Data and Analytics in Today's Business World measured?
Success measures for Big Data and Analytics in Today's Business World are agreed with you before design, as part of the ADDIE model. Bodhih can add pre- and post-program assessments on AssessAll and manager check-ins to track behaviour change.