Google Big Data Corporate Training Course

Edstellar's instructor-led Google Big Data training course offers teams an unparalleled opportunity to harness the potential of data-driven insights. From mastering advanced analytics to leveraging cloud-based infrastructure, this customized curriculum equips firms with the expertise to drive innovation and make informed business decisions.

8 - 16 hrs
Instructor-led (On-site/Virtual)
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Google Big Data Training

Drive Team Excellence with Google Big Data Corporate Training

On-site or Online Google Big Data Training - Get the best Google Big Data training from top-rated instructors to upskill your teams.

Google Big Data refers to a set of technologies and tools provided by Google Cloud Platform (GCP) that enable organizations to store, process, analyze, and derive valuable insights from large, complex datasets. Unlock the true potential of your organization's data-driven endeavors with our cutting-edge Google Big Data training course. Tailored exclusively for corporate teams, our Google Big Data instructor-led training is the gateway to mastering the art of harnessing data for strategic insights.

Designed by industry experts, our Google Big Data training delves into the heart of data management, analytics, and visualization, equipping the team with the skills needed to extract actionable intelligence from vast datasets. Attendees will learn how to navigate the intricate landscape of Google Big Data tools and techniques through immersive, hands-on exercises and real-world scenarios. We offer onsite Google Big Data training, ensuring seamless integration of newfound skills into the existing workflows. Elevate the team's proficiency and drive unparalleled growth with our dynamic training that's as innovative as the technology it covers.

Google Big Data Training for Employees: Key Learning Outcomes

Develop essential skills from Edstellar, an industry-recognized Google Big Data training provider. Professionals who complete Google Big Data training will be able to:

  • Apply big data concepts and techniques to real-world scenarios
  • Implement scalable data pipelines for efficient data management
  • Optimize data workflows and enhance data governance practices
  • Create meaningful data visualizations to communicate insights effectively
  • Utilize Google Cloud Platform tools and services for data processing and analysis
  • Perform statistical analysis and apply machine learning algorithms to derive insights from large datasets

Key Benefits of the Training

Following are some of the key benefits of Edstellar's onsite / virtual Google Big Data training:

  • Comprehensive understanding of big data concepts and techniques
  • Ability to build scalable data pipelines for efficient data management
  • Empowered employees to drive innovation and identify business opportunities
  • Optimization of data workflows and enhancement of data governance practices
  • Creation of impactful data visualizations for effective communication of insights
  • Proficiency in utilizing Google Cloud Platform tools for data processing and analysis
  • Application of advanced analytics and machine learning algorithms to derive insights

Google Big Data Training Topics and Outline

Our virtual and on-premise Google Big Data training curriculum is designed by experts according to current industry requirements. This training program provides an interactive learning experience focused on the dynamic demands of the field, making it relevant and practical for every participant.

  1. Basics of big data and its significance
    • Definition of big data
    • Characteristics of big data (volume, velocity, variety, veracity)
    • Importance of big data in decision-making and business insights
  2. Introduction to Google Cloud Platform (GCP)
    • Overview of Google Cloud Platform services
    • Advantages of using GCP for big data management
    • Introduction to key GCP services like Google Cloud Storage, Google BigQuery, and Google Cloud Dataflow
  3. Google Cloud services for big data management and analysis
    • Google Cloud Storage for scalable and cost-effective data storage
    • Google BigQuery for querying and analyzing large datasets
    • Google Cloud Dataflow for building data pipelines and data processing
  1. Integrating big data and machine learning concepts
    • Understanding the relationship between big data and machine learning
    • Leveraging big data for training and improving machine learning models
    • Real-world examples of big data-driven machine learning applications
  2. Google Cloud services for big data and machine learning workflows
    • Introduction to Google Cloud Dataproc for big data processing
    • Google Cloud ML Engine for training and deploying machine learning models
    • Integration of big data and machine learning workflows using GCP services
  3. Applying machine learning algorithms to big data analysis
    • Supervised learning algorithms (e.g., linear regression, logistic regression, decision trees)
    • Unsupervised learning algorithms (e.g., clustering, dimensionality reduction)
    • Techniques for feature engineering and model evaluation in big data scenarios
  1. Understanding streaming data and its characteristics
    • Introduction to real-time data and its importance
    • Key challenges in handling streaming data (timeliness, data volume, data quality)
    • Concepts of event time and processing time in streaming data
  2. Data ingestion and processing techniques for real-time data
    • Streaming data ingestion using Google Cloud Pub/Sub
    • Real-time data processing using Apache Beam and Google Cloud Dataflow
    • Windowing and triggering mechanisms for processing streaming data
  3. Building data pipelines for streaming data handling
    • Designing scalable and fault-tolerant data pipelines for streaming data
    • Transformation and aggregation operations on streaming data
    • Handling late data and out-of-order events in streaming pipelines
  1. Introduction to Google BigQuery as a data warehouse solution
    • Overview of Google BigQuery features and benefits
    • Introduction to BigQuery's architecture and query execution model
    • Understanding datasets, tables, and schema design in BigQuery
  2. Querying and analyzing large datasets using BigQuery
    • Writing SQL queries in BigQuery for data exploration and analysis
    • Filtering, aggregating, and joining data in BigQuery
    • Advanced querying techniques and functions in BigQuery
  3. Query performance optimization and cost management in BigQuery
    • Techniques for optimizing query performance in BigQuery
    • Understanding query caching and query plan optimization
    • Cost management strategies for efficient usage of BigQuery resources
  1. Overview of machine learning options on Google Cloud
    • Introduction to Google Cloud AutoML for automated machine learning
    • Google Cloud AI Platform for end-to-end machine learning workflows
    • Other machine learning tools and frameworks available on GCP
  2. Supervised and unsupervised learning techniques
    • Understanding the concepts of supervised and unsupervised learning
    • Overview of popular supervised learning algorithms (e.g., linear regression, random forests, neural networks)
    • Introduction to unsupervised learning algorithms (e.g., clustering, dimensionality reduction)
  3. Implementing machine learning algorithms with Google Cloud tools
    • Training and deploying machine learning models using Google Cloud AI Platform
    • Evaluating and monitoring machine learning models on GCP
    • Integrating machine learning models with other GCP services for real-world applications
  1. End-to-end machine learning workflow using Vertex AI
    • Overview of the machine learning workflow stages (data preparation, model training, evaluation, deployment)
    • Introduction to Vertex AI as a unified machine learning platform on Google Cloud
  2. Data preparation and preprocessing for machine learning
    • Exploratory data analysis and feature engineering techniques
    • Data preprocessing steps like normalization, scaling, and handling missing values
    • Splitting datasets into training, validation, and test sets
  3. Building, training, and deploying machine learning models with Vertex AI
    • Configuring machine learning models using Vertex AI tools and libraries
    • Training and hyperparameter tuning of models with Vertex AI training jobs
    • Deploying trained models as endpoints for prediction and inference

This Corporate Training for Google Big Data is ideal for:

What Sets Us Apart?

Google Big Data Corporate Training Prices

Elevate your team's Google Big Data skills with our Google Big Data corporate training course. Choose from transparent pricing options tailored to your needs. Whether you have a training requirement for a small group or for large groups, our training solutions have you covered.

Request for a quote to know about our Google Big Data corporate training cost and plan the training initiative for your teams. Our cost-effective Google Big Data training pricing ensures you receive the highest value on your investment.

Request for a Quote

Our customized corporate training packages offer various benefits. Maximize your organization's training budget and save big on your Google Big Data training by choosing one of our training packages. This option is best suited for organizations with multiple training requirements. Our training packages are a cost-effective way to scale up your workforce skill transformation efforts..

Starter Package

125 licenses

64 hours of training (includes VILT/In-person On-site)

Tailored for SMBs

Most Popular
Growth Package

350 licenses

160 hours of training (includes VILT/In-person On-site)

Ideal for growing SMBs

Enterprise Package

900 licenses

400 hours of training (includes VILT/In-person On-site)

Designed for large corporations

Custom Package

Unlimited licenses

Unlimited duration

Designed for large corporations

View Corporate Training Packages

This Corporate Training for Google Big Data is ideal for:

Edstellar's instructor-led Google Big Data Training is designed for organizations/learning and development departments looking to upskill

data analysts, business analysts, cloud data engineers, business intelligence professionals, other developers, and marketing professionals.

Prerequisites for Google Big Data Training

Edstellar's instructor-led Google Big Data Training requires knowledge of basic Big Data and cloud technologies.

Assess the Training Effectiveness

Bringing you the Best Google Big Data Trainers in the Industry

The instructor-led Google Big Data Training training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Google Big Data practices.

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