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Big Data Analytics for Business Intelligence (BI)

This program aims to provide participants with essential knowledge and resources to effectively utilize big data for enhanced Business Intelligence (BI) applications.

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Certificate :

After Completion

Start Date :

10-Jan-2025

Duration :

30 Days

Course fee :

$150

COURSE DESCRIPTION:

– This program aims to provide participants with essential knowledge and resources to effectively utilize big data for enhanced Business Intelligence (BI) applications.
– Participants will delve into the methodologies for integrating, processing, and analyzing extensive datasets through the use of state-of-the-art technologies.
– The course emphasizes the development of scalable solutions that produce actionable insights, facilitating informed decision-making within organizational contexts.
– By the conclusion of the program, attendees will possess the confidence to implement big data analytics strategies, thereby improving their BI proficiency.
– This training is structured to empower individuals to leverage data-driven approaches, ultimately transforming their enterprise operations and strategic initiatives.

CERTIFICATION:

  1. Participants will receive a Certificate in Big Data Analytics for Business Intelligence, validating their expertise in leveraging big data for advanced BI solutions.

LEARNING OUTCOMES:

By the conclusion of the course, participants will possess the skills to:

– Grasp the essential principles of big data and its significance in business intelligence (BI) frameworks.
– Utilize various big data tools and technologies, including Hadoop, Spark, and NoSQL databases, to enhance data management capabilities.
– Conduct large-scale data ingestion, processing, and analytical operations to derive meaningful insights.
– Employ sophisticated BI visualization tools, such as Power BI and Tableau, to present big data findings effectively.
– Develop and optimize data pipelines to facilitate real-time analytics, ensuring that big data architectures are tailored to meet specific business needs.

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Course Curriculum

Introduction to Big Data and BI
  1. What is big data? Characteristics and use cases
  2. The role of big data in enhancing BI capabilities
  3. Overview of big data architectures: Batch processing, real-time processing, and hybrid models
  4. Challenges and opportunities in big data analytics for BI
Big Data Tools and Technologies
  1. Hadoop ecosystem: HDFS, MapReduce, Hive, and Pig
  2. Apache Spark: Fast data processing and analytics
  3. NoSQL databases: MongoDB, Cassandra, and HBase
  4. Cloud-based big data solutions: AWS, Azure, and Google Cloud
Data Ingestion and Integration
  1. Collecting data from diverse sources: Structured, unstructured, and semi-structured data
  2. Tools for data ingestion: Apache Kafka, Flume, and Sqoop
  3. ETL/ELT processes for big data environments
  4. Real-world examples: Building data pipelines for enterprise use cases
Big Data Processing and Storage
  1. Processing large-scale data with Spark and Hadoop
  2. Distributed data storage systems: HDFS, Amazon S3, and Google BigQuery
  3. Implementing data partitioning and indexing for performance optimization
  4. Hands-on activity: Querying big data with Hive and Spark SQL
Advanced Analytics and Visualization
  1. Using BI tools for big data visualization: Power BI, Tableau, and Looker
  2. Creating dashboards for large-scale datasets
  3. Real-time analytics and alert systems for business intelligence
  4. Case study: Building a big data dashboard for customer analytics
Predictive Analytics and Machine Learning
  1. Applying machine learning techniques to big data
  2. Tools for scalable machine learning: MLlib, TensorFlow, and PySpark
  3. Real-world use cases: Customer segmentation, fraud detection, and demand forecasting
  4. Hands-on activity: Implementing a predictive analytics model on a big data platform
Real-Time Data Processing and Analytics
  1. Streaming data technologies: Apache Kafka, Spark Streaming, and Flink
  2. Building real-time BI dashboards for time-sensitive decisions
  3. Use cases: Monitoring IoT data, financial transactions, and social media trends
  4. Practical implementation: Setting up a real-time analytics pipeline
Designing a Big Data Strategy
  1. Aligning big data initiatives with business objectives
  2. Evaluating ROI of big data projects
  3. Best practices for scalability, security, and governance in big data environments
  4. Capstone project: Develop a big data BI strategy for a specific business scenario

Training Features

Video Tutorials

Step-by-step guidance on big data tools and BI integration.

Interactive Exercises

Practical tasks for processing and visualizing big data.

Downloadable Resources

Cheat sheets, architecture diagrams, and sample datasets.

Capstone Project

Design and execute a real-world big data BI solution.

Community Forum

Collaborate with peers and industry experts.

Certification

A globally recognized certificate upon completing the course.

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